2270:. A successful data model will accurately reflect the possible state of the external world being modeled: for example, if people can have more than one phone number, it will allow this information to be captured. Designing a good conceptual data model requires a good understanding of the application domain; it typically involves asking deep questions about the things of interest to an organization, like "can a customer also be a supplier?", or "if a product is sold with two different forms of packaging, are those the same product or different products?", or "if a plane flies from New York to Dubai via Frankfurt, is that one flight or two (or maybe even three)?". The answers to these questions establish definitions of the terminology used for entities (customers, products, flights, flight segments) and their relationships and attributes.
1964:, the data used remains in its original locations and real-time access is established to allow analytics across multiple sources. This can aid in resolving some technical difficulties such as compatibility problems when combining data from various platforms, lowering the risk of error caused by faulty data, and guaranteeing that the newest data is used. Furthermore, avoiding the creation of a new database containing personal information can make it easier to comply with privacy regulations. However, with data virtualization, the connection to all necessary data sources must be operational as there is no local copy of the data, which is one of the main drawbacks of the approach.
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intact. Thus, the database's conceptual and external architectural levels should be maintained in the transformation. It may be desired that also some aspects of the architecture internal level are maintained. A complex or large database migration may be a complicated and costly (one-time) project by itself, which should be factored into the decision to migrate. This is in spite of the fact that tools may exist to help migration between specific DBMSs. Typically, a DBMS vendor provides tools to help import databases from other popular DBMSs.
1891:(e.g., memory and external storage). The database data and the additional needed information, possibly in very large amounts, are coded into bits. Data typically reside in the storage in structures that look completely different from the way the data look at the conceptual and external levels, but in ways that attempt to optimize (the best possible) these levels' reconstruction when needed by users and programs, as well as for computing additional types of needed information from the data (e.g., when querying the database).
231:– Selecting data according to specified criteria (e.g., a query, a position in a hierarchy, or a position in relation to other data) and providing that data either directly to the user, or making it available for further processing by the database itself or by other applications. The retrieved data may be made available in a more or less direct form without modification, as it is stored in the database, or in a new form obtained by altering it or combining it with existing data from the database.
2510:
937:, the creator of dBASE, stated: "dBASE was different from programs like BASIC, C, FORTRAN, and COBOL in that a lot of the dirty work had already been done. The data manipulation is done by dBASE instead of by the user, so the user can concentrate on what he is doing, rather than having to mess with the dirty details of opening, reading, and closing files, and managing space allocation." dBASE was one of the top selling software titles in the 1980s and early 1990s.
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2333:, meaning that the decisions made for performance optimization purposes should be invisible to end-users and applications. There are two types of data independence: Physical data independence and logical data independence. Physical design is driven mainly by performance requirements, and requires a good knowledge of the expected workload and access patterns, and a deep understanding of the features offered by the chosen DBMS.
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desired database state (i.e., the values of its data and their embedding in database's data structures) is kept within dedicated backup files (many techniques exist to do this effectively). When it is decided by a database administrator to bring the database back to this state (e.g., by specifying this state by a desired point in time when the database was in this state), these files are used to restore that state.
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it called "subschemas". For example, an employee database can contain all the data about an individual employee, but one group of users may be authorized to view only payroll data, while others are allowed access to only work history and medical data. If the DBMS provides a way to interactively enter and update the database, as well as interrogate it, this capability allows for managing personal databases.
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principle every level, and even every external view, can be presented by a different data model. In practice usually a given DBMS uses the same data model for both the external and the conceptual levels (e.g., relational model). The internal level, which is hidden inside the DBMS and depends on its implementation, requires a different level of detail and uses its own types of data structure types.
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language that expressed what data was required, rather than the access path by which it should be found. Finding an efficient access path to the data became the responsibility of the database management system, rather than the application programmer. This process, called query optimization, depended on the fact that queries were expressed in terms of mathematical logic.
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1157:, document-text, statistical, or multimedia objects. Another way is by their application area, for example: accounting, music compositions, movies, banking, manufacturing, or insurance. A third way is by some technical aspect, such as the database structure or interface type. This section lists a few of the adjectives used to characterize different kinds of databases.
479:
682:; because these operations have clean mathematical properties, it becomes possible to rewrite queries in provably correct ways, which is the basis of query optimization. There is no loss of expressiveness compared with the hierarchic or network models, though the connections between tables are no longer so explicit.
2029:(e.g., query types, or specific queries), or using specific access paths to the former (e.g., using specific indexes or other data structures to access information). Database access controls are set by special authorized (by the database owner) personnel that uses dedicated protected security DBMS interfaces.
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Tools or hooks for database design, application programming, application program maintenance, database performance analysis and monitoring, database configuration monitoring, DBMS hardware configuration (a DBMS and related database may span computers, networks, and storage units) and related database
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Database access control deals with controlling who (a person or a certain computer program) are allowed to access what information in the database. The information may comprise specific database objects (e.g., record types, specific records, data structures), certain computations over certain objects
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database is intended to store in a manageable and protected way diverse objects that do not fit naturally and conveniently in common databases. It may include email messages, documents, journals, multimedia objects, etc. The name may be misleading since some objects can be highly structured. However,
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archive data from operational databases and often from external sources such as market research firms. The warehouse becomes the central source of data for use by managers and other end-users who may not have access to operational data. For example, sales data might be aggregated to weekly totals and
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As well as identifying rows/records using logical identifiers rather than disk addresses, Codd changed the way in which applications assembled data from multiple records. Rather than requiring applications to gather data one record at a time by navigating the links, they would use a declarative query
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In the hierarchic and network models, records were allowed to have a complex internal structure. For example, the salary history of an employee might be represented as a "repeating group" within the employee record. In the relational model, the process of normalization led to such internal structures
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which was one of the major initial driving forces of the relational model. The idea is that changes made at a certain level do not affect the view at a higher level. For example, changes in the internal level do not affect application programs written using conceptual level interfaces, which reduces
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framework has been extended to the field of query languages for relational databases as a way to support sound approximation techniques. The semantics of query languages can be tuned according to suitable abstractions of the concrete domain of data. The abstraction of relational database systems has
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When the database is ready (all its data structures and other needed components are defined), it is typically populated with initial application's data (database initialization, which is typically a distinct project; in many cases using specialized DBMS interfaces that support bulk insertion) before
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later by keeping a record of access occurrences and changes. Sometimes application-level code is used to record changes rather than leaving this in the database. Monitoring can be set up to attempt to detect security breaches. Therefore, organizations must take database security seriously because of
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in the early 1970s. The first version was ready in 1974/5, and work then started on multi-table systems in which the data could be split so that all of the data for a record (some of which is optional) did not have to be stored in a single large "chunk". Subsequent multi-user versions were tested by
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The conceptual view provides a level of indirection between internal and external. On the one hand it provides a common view of the database, independent of different external view structures, and on the other hand it abstracts away details of how the data are stored or managed (internal level). In
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to groups, or (in the most elaborate models) through the assignment of individuals and groups to roles which are then granted entitlements. Data security prevents unauthorized users from viewing or updating the database. Using passwords, users are allowed access to the entire database or subsets of
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Occasionally a database employs storage redundancy by database objects replication (with one or more copies) to increase data availability (both to improve performance of simultaneous multiple end-user accesses to the same database object, and to provide resiliency in a case of partial failure of a
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It is also generally to be expected the DBMS will provide a set of utilities for such purposes as may be necessary to administer the database effectively, including import, export, monitoring, defragmentation and analysis utilities. The core part of the DBMS interacting between the database and the
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The use of primary keys (user-oriented identifiers) to represent cross-table relationships, rather than disk addresses, had two primary motivations. From an engineering perspective, it enabled tables to be relocated and resized without expensive database reorganization. But Codd was more interested
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to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data). The DBMS provides various functions that allow entry, storage and retrieval of large quantities of information and provides
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While there is typically only one conceptual and internal view of the data, there can be any number of different external views. This allows users to see database information in a more business-related way rather than from a technical, processing viewpoint. For example, a financial department of a
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as intermediates for storage layout), storage properties and configuration settings are extremely important for the efficient operation of the DBMS, and thus are closely maintained by database administrators. A DBMS, while in operation, always has its database residing in several types of storage
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For instance, a common use of a database system is to track information about users, their name, login information, various addresses and phone numbers. In the navigational approach, all of this data would be placed in a single variable-length record. In the relational approach, the data would be
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or TCOs), functional, and operational (different DBMSs may have different capabilities). The migration involves the database's transformation from one DBMS type to another. The transformation should maintain (if possible) the database related application (i.e., all related application programs)
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Sometimes it is desired to bring a database back to a previous state (for many reasons, e.g., cases when the database is found corrupted due to a software error, or if it has been updated with erroneous data). To achieve this, a backup operation is done occasionally or continuously, where each
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accelerator, a hardware disk controller with programmable search capabilities. In the long term, these efforts were generally unsuccessful because specialized database machines could not keep pace with the rapid development and progress of general-purpose computers. Thus most database systems
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document attributes. XML databases are mostly used in applications where the data is conveniently viewed as a collection of documents, with a structure that can vary from the very flexible to the highly rigid: examples include scientific articles, patents, tax filings, and personnel records.
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Codd used mathematical terms to define the model: relations, tuples, and domains rather than tables, rows, and columns. The terminology that is now familiar came from early implementations. Codd would later criticize the tendency for practical implementations to depart from the mathematical
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Increasingly, there are calls for a single system that incorporates all of these core functionalities into the same build, test, and deployment framework for database management and source control. Borrowing from other developments in the software industry, some market such offerings as
953:. That is to say that if a person's data were in a database, that person's attributes, such as their address, phone number, and age, were now considered to belong to that person instead of being extraneous data. This allows for relations between data to be related to objects and their
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or query results. Storing such views saves the expensive computing them each time they are needed. The downsides of materialized views are the overhead incurred when updating them to keep them synchronized with their original updated database data, and the cost of storage redundancy.
586:. IMS was generally similar in concept to CODASYL, but used a strict hierarchy for its model of data navigation instead of CODASYL's network model. Both concepts later became known as navigational databases due to the way data was accessed: the term was popularized by Bachman's 1973
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the many benefits it provides. Organizations will be safeguarded from security breaches and hacking activities like firewall intrusion, virus spread, and ransom ware. This helps in protecting the company's essential information, which cannot be shared with outsiders at any cause.
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by which the rows of the table could be uniquely identified; cross-references between tables always used these primary keys, rather than disk addresses, and queries would join tables based on these key relationships, using a set of operations based on the mathematical system of
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system performs many of the functions of a general-purpose DBMS such as message insertion, message deletion, attachment handling, blocklist lookup, associating messages an email address and so forth however these functions are limited to what is required to handle email.
2092:, etc.), an abstraction supported in database and also other systems. Each transaction has well defined boundaries in terms of which program/code executions are included in that transaction (determined by the transaction's programmer via special transaction commands).
2536:) unifies the various external views into a compatible global view. It provides the synthesis of all the external views. It is out of the scope of the various database end-users, and is rather of interest to database application developers and database administrators.
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comprises several distinct databases, each with its own DBMS. It is handled as a single database by a federated database management system (FDBMS), which transparently integrates multiple autonomous DBMSs, possibly of different types (in which case it would also be a
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A database built with one DBMS is not portable to another DBMS (i.e., the other DBMS cannot run it). However, in some situations, it is desirable to migrate a database from one DBMS to another. The reasons are primarily economical (different DBMSs may have different
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The most popular database model for general-purpose databases is the relational model, or more precisely, the relational model as represented by the SQL language. The process of creating a logical database design using this model uses a methodical approach known as
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expressed in the form of a schema. Whereas the conceptual data model is (in theory at least) independent of the choice of database technology, the logical data model will be expressed in terms of a particular database model supported by the chosen DBMS. (The terms
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deals with all various aspects of protecting the database content, its owners, and its users. It ranges from protection from intentional unauthorized database uses to unintentional database accesses by unauthorized entities (e.g., a person or a computer program).
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includes an event-driven architecture which can respond to conditions both inside and outside the database. Possible uses include security monitoring, alerting, statistics gathering and authorization. Many databases provide active database features in the form of
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using funding that had already been allocated for a geographical database project and student programmers to produce code. Beginning in 1973, INGRES delivered its first test products which were generally ready for widespread use in 1979. INGRES was similar to
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systems. He was unhappy with the navigational model of the CODASYL approach, notably the lack of a "search" facility. In 1970, he wrote a number of papers that outlined a new approach to database construction that eventually culminated in the groundbreaking
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to be used by database administrators to define the needed application's data structures within the DBMS's respective data model. Other user interfaces are used to select needed DBMS parameters (like security related, storage allocation parameters, etc.).
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Often DBMSs will have configuration parameters that can be statically and dynamically tuned, for example the maximum amount of main memory on a server the database can use. The trend is to minimize the amount of manual configuration, and for cases such as
237:– Registering and monitoring users, enforcing data security, monitoring performance, maintaining data integrity, dealing with concurrency control, and recovering information that has been corrupted by some event such as an unexpected system failure.
85:, and the database itself to capture and analyze the data. The DBMS additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a
2555:), computed from generic data, if performance justification exists for such redundancy. It balances all the external views' performance requirements, possibly conflicting, in an attempt to optimize overall performance across all activities.
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in the difference in semantics: the use of explicit identifiers made it easier to define update operations with clean mathematical definitions, and it also enabled query operations to be defined in terms of the established discipline of
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in the organization. This can help to establish what information is needed in the database, and what can be left out. For example, it can help when deciding whether the database needs to hold historic data as well as current data.
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are used by the storage engine to serialize the data model so it can be written to the medium of choice. Techniques such as indexing may be used to improve performance. Conventional storage is row-oriented, but there are also
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is used as a synonym for federated database, though it may refer to a less integrated (e.g., without an FDBMS and a managed integrated schema) group of databases that cooperate in a single application. In this case, typically
494:
coincided with the availability of direct-access storage (disks and drums) from the mid-1960s onwards. The term represented a contrast with the tape-based systems of the past, allowing shared interactive use rather than daily
1169:, but is typically backed-up by non-volatile computer data storage. Main memory databases are faster than disk databases, and so are often used where response time is critical, such as in telecommunications network equipment.
407:. Only in the mid-1980s did computing hardware become powerful enough to allow the wide deployment of relational systems (DBMSs plus applications). By the early 1990s, however, relational systems dominated in all large-scale
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from the internal level when needed. Databases as digital objects contain three layers of information which must be stored: the data, the structure, and the semantics. Proper storage of all three layers is needed for future
802:
In the 1970s and 1980s, attempts were made to build database systems with integrated hardware and software. The underlying philosophy was that such integration would provide higher performance at a lower cost. Examples were
1255:
End-user databases consist of data developed by individual end-users. Examples of these are collections of documents, spreadsheets, presentations, multimedia, and other files. Several products exist to support such
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system is a DBMS which is tightly integrated with an application software that requires access to stored data in such a way that the DBMS is hidden from the application's end-users and requires little or no ongoing
969:
attempt to solve this problem by providing an object-oriented language (sometimes as extensions to SQL) that programmers can use as alternative to purely relational SQL. On the programming side, libraries known as
1029:, availability, and partition tolerance guarantees. A distributed system can satisfy any two of these guarantees at the same time, but not all three. For that reason, many NoSQL databases are using what is called
2547:) is the internal organization of data inside a DBMS. It is concerned with cost, performance, scalability and other operational matters. It deals with storage layout of the data, using storage structures such as
510:
As computers grew in speed and capability, a number of general-purpose database systems emerged; by the mid-1960s a number of such systems had come into commercial use. Interest in a standard began to grow, and
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to allow applications to be written to interact with and manipulate the database. A special purpose DBMS may use a private API and be specifically customized and linked to a single application. For example, an
1039:
is a class of modern relational databases that aims to provide the same scalable performance of NoSQL systems for online transaction processing (read-write) workloads while still using SQL and maintaining the
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After designing a database for an application, the next stage is building the database. Typically, an appropriate general-purpose DBMS can be selected to be used for this purpose. A DBMS provides the needed
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SQL combines the roles of data definition, data manipulation, and query in a single language. It was one of the first commercial languages for the relational model, although it departs in some respects from
641:", each table being used for a different type of entity. Each table would contain a fixed number of columns containing the attributes of the entity. One or more columns of each table were designated as a
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876:) started from a different chain, based on IBM's papers on System R. Though Oracle V1 implementations were completed in 1978, it was not until Oracle Version 2 when Ellison beat IBM to market in 1979.
329:
The sizes, capabilities, and performance of databases and their respective DBMSs have grown in orders of magnitude. These performance increases were enabled by the technology progress in the areas of
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the entire possible object collection does not fit into a predefined structured framework. Most established DBMSs now support unstructured data in various ways, and new dedicated DBMSs are emerging.
2047:), or the interpretation of them, or parts of them to meaningful information (e.g., by looking at the strings of bits that they comprise, concluding specific valid credit-card numbers; e.g., see
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nowadays are software systems running on general-purpose hardware, using general-purpose computer data storage. However, this idea is still pursued in certain applications by some companies like
1507:
Connolly and Begg define database management system (DBMS) as a "software system that enables users to define, create, maintain and control access to the database." Examples of DBMS's include
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The final stage of database design is to make the decisions that affect performance, scalability, recovery, security, and the like, which depend on the particular DBMS. This is often called
694:
into a user table, an address table and a phone number table (for instance). Records would be created in these optional tables only if the address or phone numbers were actually provided.
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can be stored, organized, and manipulated. The most popular example of a database model is the relational model (or the SQL approximation of relational), which uses a table-based format.
538:
The CODASYL approach offered applications the ability to navigate around a linked data set which was formed into a large network. Applications could find records by one of three methods:
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that record contact, credit, and demographic information about a business's customers, personnel databases that hold information such as salary, benefits, skills data about employees,
1192:. Both the database and most of its DBMS reside remotely, "in the cloud", while its applications are both developed by programmers and later maintained and used by end-users through a
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databases attempted new implementations that retained the relational/SQL model while aiming to match the high performance of NoSQL compared to commercially available relational DBMSs.
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The large major enterprise DBMSs have tended to increase in size and functionality and have involved up to thousands of human years of development effort throughout their lifetime.
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is designed for storing, retrieving, and managing document-oriented, or semi structured, information. Document-oriented databases are one of the main categories of NoSQL databases.
2318:. The goal of normalization is to ensure that each elementary "fact" is only recorded in one place, so that insertions, updates, and deletions automatically maintain consistency.
854:– SQL – had been added. Codd's ideas were establishing themselves as both workable and superior to CODASYL, pushing IBM to develop a true production version of System R, known as
2166:) for better performance; application's data structures may be changed or added, new related application programs may be written to add to the application's functionality, etc.
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2088:. A database transaction is a unit of work, typically encapsulating a number of operations over a database (e.g., reading a database object, writing, acquiring or releasing a
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systems that record details about product components, parts inventory, and financial databases that keep track of the organization's money, accounting and financial dealings.
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with nodes, edges, and properties to represent and store information. General graph databases that can store any graph are distinct from specialized graph databases such as
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After the database is created, initialized and populated it needs to be maintained. Various database parameters may need changing and the database may need to be tuned (
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1771:(ISO) in 1987. The standards have been regularly enhanced since and are supported (with varying degrees of conformance) by all mainstream commercial relational DBMSs.
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company needs the payment details of all employees as part of the company's expenses, but does not need details about employees that are in the interest of the
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was a development where the application resided on a client desktop and the database on a server allowing the processing to be distributed. This evolved into a
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to that object. Hypertext databases are particularly useful for organizing large amounts of disparate information. For example, they are useful for organizing
403:
should search for data by content, rather than by following links. The relational model employs sets of ledger-style tables, each used for a different type of
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disk arrays used for stable storage. Hardware database accelerators, connected to one or more servers via a high-speed channel, are also used in large-volume
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Databases are used to hold administrative information and more specialized data, such as engineering data or economic models. Examples include computerized
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Because of the close relationship between them, the term "database" is often used casually to refer to both a database and the DBMS used to manipulate it.
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distributed database). Updates of a replicated object need to be synchronized across the object copies. In many cases, the entire database is replicated.
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can store the data with multidimensional features. The queries on such data include location-based queries, like "Where is the closest hotel in my area?".
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defines how each group of end-users sees the organization of data in the database. A single database can have any number of views at the external level.
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Formally, a "database" refers to a set of related data accessed through the use of a "database management system" (DBMS), which is an integrated set of
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making it operational. In some cases, the database becomes operational while empty of application data, and data are accumulated during its operation.
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Existing DBMSs provide various functions that allow management of a database and its data which can be classified into four main functional groups:
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to provide alternate access paths. Many CODASYL databases also added a declarative query language for end users (as distinct from the navigational
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Change and access logging records who accessed which attributes, what was changed, and when it was changed. Logging services allow for a forensic
89:. Often the term "database" is also used loosely to refer to any of the DBMS, the database system or an application associated with the database.
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that allows users to execute SQL queries textually or graphically, to a website that happens to use a database to store and search information.
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as it emphasized a more familiar description than the earlier relational model. Later on, entity–relationship constructs were retrofitted as a
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a.k.a. "storage engine". Though typically accessed by a DBMS through the underlying operating system (and often using the operating systems'
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that implements the relevant data structures within the database. This process is often called logical database design, and the output is a
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A database model is a type of data model that determines the logical structure of a database and fundamentally determines in which manner
1431:, where each processing unit (typically consisting of multiple processors) has its own main memory, but all units share the other storage.
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Databases are used to support internal operations of organizations and to underpin online interactions with customers and suppliers (see
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in general deals with protecting specific chunks of data, both physically (i.e., from corruption, or destruction, or removal; e.g., see
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In recent years, there has been a strong demand for massively distributed databases with high partition tolerance, but according to the
2972:"IBM Information Management System (IMS) 13 Transaction and Database Servers delivers high performance and low total cost of ownership"
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883:. PostgreSQL is often used for global mission-critical applications (the .org and .info domain name registries use it as their primary
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In this paper, he described a new system for storing and working with large databases. Instead of records being stored in some sort of
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949:, saw a growth in how data in various databases were handled. Programmers and designers began to treat the data in their databases as
431:. The dominant database language, standardized SQL for the relational model, has influenced database languages for other data models.
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673:, records are "linked" using virtual keys not stored in the database but defined as needed between the data contained in the records.
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database, any word or a piece of text representing an object, e.g., another piece of text, an article, a picture, or a film, can be
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2224:(a partial order (tree) of operations) to be executed to compute the query result. May be specific to a particular storage engine.
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Static analysis techniques for software verification can be applied also in the scenario of query languages. In particular, the *
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are dedicated computers that hold the actual databases and run only the DBMS and related software. Database servers are usually
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External interaction with the database will be via an application program that interfaces with the DBMS. This can range from a
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The functionality provided by a DBMS can vary enormously. The core functionality is the storage, retrieval and update of data.
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3579:(Technical report). CONCOMP (Research in Conversational Use of Computers) Project. University of Michigan. Technical Report 6.
3562:(Technical report). CONCOMP (Research in Conversational Use of Computers) Project. University of Michigan. Technical Report 3.
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many interesting applications, in particular, for security purposes, such as fine-grained access control, watermarking, etc.
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Database languages are special-purpose languages, which allow one or more of the following tasks, sometimes distinguished as
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store detailed data about the operations of an organization. They typically process relatively high volumes of updates using
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1550:. Other extensions can indicate some other characteristics, such as DDBMS for a distributed database management systems.
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4504:
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4317:
4093:
4078:
2679:
2108:
2100:
1778:
1666:
1392:
568:). However, CODASYL databases were complex and required significant training and effort to produce useful applications.
2228:
mapping (especially for a distributed DBMS), storage allocation and database layout monitoring, storage migration, etc.
6827:
6764:
6517:
6049:
5855:
5574:
5253:
5137:
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2378:
2262:
that reflects the structure of the information to be held in the database. A common approach to this is to develop an
1902:
1435:
946:
373:
1068:
357:. The subsequent development of database technology can be divided into three eras based on data model or structure:
6887:
6472:
6433:
6349:
6044:
6009:
5778:
5768:
5544:
5396:
5269:
5165:
5085:
4976:
4625:
2417:
1803:, by relational databases with XML capability such as Oracle and Db2, and also by in-memory XML processors such as
1741:
1421:
1241:
654:) aimed to ensure that each "fact" was only stored once, thus simplifying update operations. Virtual tables called
457:
1087:
1072:
166:
for writing and querying data. In the 2000s, non-relational databases became popular, collectively referred to as
6302:
6202:
5865:
5598:
4994:
4921:
4896:
4759:
4407:
4013:
2458:
2274:
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1828:
Computations to modify query results, like counting, summing, averaging, sorting, grouping, and cross-referencing
1281:
1260:
1138:
1130:
1079:
950:
500:
272:
3162:
1606:
Early multi-user DBMS typically only allowed for the application to reside on the same computer with access via
879:
Stonebraker went on to apply the lessons from INGRES to develop a new database, Postgres, which is now known as
6665:
6223:
6218:
6176:
5952:
5355:
5160:
4845:
4678:
4264:
4133:
1735:
1487:
785:
2285:
Having produced a conceptual data model that users are happy with, the next stage is to translate this into a
6882:
6645:
6292:
5824:
5814:
5468:
5290:
4906:
4840:
4731:
4547:
4207:
2190:
2131:
1946:
1285:
1041:
330:
5527:
3927:
Physical
Database Design: the database professional's guide to exploiting indexes, views, storage, and more
1738:(DDL) – defines data types such as creating, altering, or dropping tables and the relationships among them;
209:
or a card index) as size and usage requirements typically necessitate use of a database management system.
6318:
6115:
6093:
5895:
5850:
5238:
5127:
5040:
4971:
4802:
4683:
4450:
4440:
4435:
3069:
2315:
1911:
1882:
and longevity of the database. Putting data into permanent storage is generally the responsibility of the
1615:
1448:
1384:
1314:
is a kind of NoSQL DBMS that allows modeling, storage, and retrieval of (usually large) multi-dimensional
1304:
1296:
1208:
1154:
1134:
1033:
to provide both availability and partition tolerance guarantees with a reduced level of data consistency.
954:
781:
777:
765:
730:
353:, which became widely available in the mid-1960s; earlier systems relied on sequential storage of data on
198:
290:, computer and storage vendors often take into account DBMS requirements in their own development plans.
245:. "Database system" refers collectively to the database model, database management system, and database.
6872:
6465:
6410:
6277:
6019:
5870:
5312:
4941:
4911:
4901:
4797:
4711:
4587:
4527:
4494:
4484:
4367:
4332:
4322:
4259:
4128:
4103:
4098:
4063:
3058:. Institute of Labor and Industrial Relations (ILIR), University of Michigan and Wayne State University.
2373:
2259:
2073:
2033:
1879:
1844:
1774:
1729:
1361:
1022:
773:
595:
516:
473:
358:
338:
269:
125:
5624:
3319:
Paiho, Satu; Tuominen, Pekka; Rökman, Jyri; Ylikerälä, Markus; Pajula, Juha; Siikavirta, Hanne (2022).
658:
could present the data in different ways for different users, but views could not be directly updated.
3573:
Feasibility of a set-theoretic data structure: a general structure based on a reconstituted definition
6680:
6675:
6282:
6197:
6065:
6014:
5923:
5860:
5742:
5712:
5581:
5532:
5386:
5248:
5105:
4701:
4673:
4645:
4640:
4469:
4445:
4397:
4380:
4375:
4357:
4347:
4342:
4304:
4254:
4249:
4166:
4112:
3908:
2671:
2498:
1907:
1697:. The particular API or language chosen will need to be supported by DBMS, possibly indirectly via a
1682:
1660:
1520:
1380:
1357:
1315:
1234:
1030:
719:
618:
520:
424:
400:
293:
Databases and DBMSs can be categorized according to the database model(s) that they support (such as
265:
129:
82:
3414:
1006:
databases are often very fast, do not require fixed table schemas, avoid join operations by storing
453:
6604:
6233:
6171:
6088:
6039:
5880:
5773:
5758:
5685:
5510:
5406:
5110:
4966:
4891:
4807:
4792:
4557:
4337:
4294:
4289:
4186:
4176:
4148:
3672:
2640:
2609:
2483:
2436:
2326:
2068:
1961:
1747:
1557:
proposed the following functions and services a fully-fledged general purpose DBMS should provide:
1334:
1119:
702:
647:
362:
294:
147:
139:
121:
2777:
This article quotes a development time of five years involving 750 people for DB2 release 9 alone.
1853:
Database storage is the container of the physical materialization of a database. It comprises the
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6700:
6589:
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5875:
5819:
5788:
5737:
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4706:
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2744:
2613:
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1895:
1619:
1458:
1403:
1223:
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data. Some basic and essential components of data warehousing include extracting, analyzing, and
1162:
1011:
933:. The dBASE product was lightweight and easy for any computer user to understand out of the box.
895:
531:. In 1971, the Database Task Group delivered their standard, which generally became known as the
287:
249:
31:
5629:
3966:
2251:
1760:
219:– Creation, modification and removal of definitions that detail how the data is to be organized.
3112:
Development of an object-oriented DBMS; Portland, Oregon, United States; Pages: 472–482; 1986;
2509:
1368:. Also a collection of data representing problems with their solutions and related experiences.
6943:
6730:
6650:
6609:
6599:
6563:
6145:
5695:
5549:
5411:
5391:
5210:
5187:
5033:
4951:
4881:
4860:
4822:
4630:
4597:
4577:
4269:
4181:
4055:
3948:
3930:
3868:
3840:
3821:
3800:
3762:
3722:
3684:
3658:
3593:
3585:
3511:
3383:
3373:
3342:
3113:
2552:
2330:
2085:
2044:
2021:
2016:
1988:
1923:
1831:
Constraint enforcement (e.g. in an automotive database, only allowing one engine type per car)
1638:
1607:
1597:
1494:
1472:
1414:
1399:
1280:
is used for distribution, which typically includes an atomic commit protocol (ACP), e.g., the
1248:
1227:
1026:
913:
construct for the relational model, and the difference between the two has become irrelevant.
812:
650:(from which the model takes its name). Splitting the data into a set of normalized tables (or
155:
117:
97:
2032:
This may be managed directly on an individual basis, or by the assignment of individuals and
961:" described the inconvenience of translating between programmed objects and database tables.
6923:
6527:
6328:
6034:
5885:
5732:
5722:
5690:
5300:
5120:
5090:
4784:
4668:
4635:
4430:
4352:
4241:
4227:
4222:
4171:
4158:
4083:
4036:
3745:
3714:
3633:
3492:
3332:
2719:
2624:
2548:
2468:
2395:
1763:(for example, the rows and columns of a table can be ordered). SQL became a standard of the
1539:
1528:
1465:
1219:
data, transforming, loading, and managing data so as to make them available for further use.
1178:
934:
922:
797:
670:
638:
496:
441:, which led to the coining of the term "post-relational" and also the development of hybrid
392:
342:
302:
280:
276:
187:
159:
58:
3100:
2853:
1834:
Application programming interface version of the query language, for programmer convenience
1782:
6799:
6778:
6725:
6695:
6614:
6594:
6584:
6228:
6192:
6131:
6083:
5793:
5763:
5717:
5498:
5295:
5243:
5220:
5132:
5100:
5095:
5075:
4855:
4749:
4721:
4615:
4567:
4552:
4537:
4392:
4387:
4327:
4217:
4191:
4143:
4088:
3896:
3567:
3550:
3526:
3476:
3444:
3302:"Database Preservation Toolkit: A flexible tool to normalize and give access to databases"
3136:
2734:
2714:
2655:
2597:
2561:
2412:
2286:
2246:
2215:
2212:
Graphics component for producing graphs and charts, especially in a data warehouse system.
2163:
2144:
2089:
2077:
2048:
1928:
Often storage redundancy is employed to increase performance. A common example is storing
1883:
1848:
1589:
1565:
1524:
1374:
1189:
1173:
1007:
962:
906:
873:
761:
512:
434:
416:
408:
350:
334:
133:
105:
2340:
to database objects as well as defining security levels and methods for the data itself.
1479:. More specifically the temporal aspects usually include valid-time and transaction-time.
637:
of free-form records as in CODASYL, Codd's idea was to organize the data as a number of "
1461:
process transactions fast enough for the result to come back and be acted on right away.
6532:
5975:
5845:
5783:
5727:
5700:
5593:
5554:
5307:
5200:
5170:
5080:
4961:
4865:
4764:
4610:
4582:
3912:
3677:
3618:
2749:
2699:
2443:
2388:
2349:
2337:
2151:
2124:
2081:
2055:
1866:
1535:
1475:
has built-in time aspects, for example a temporal data model and a temporal version of
1425:, where multiple processors share the main memory space, as well as other data storage.
1345:
1338:
1292:
1203:
1185:
851:
603:
599:
579:
310:
253:
242:
171:
151:
143:
113:
30:
This article is about the computing concept. For instances of the general concept, see
3959:
3129:
2831:
1754:
Database languages are specific to a particular data model. Notable examples include:
621:, in one of their offshoot offices that were primarily involved in the development of
535:, and soon a number of commercial products based on this approach entered the market.
507:
of
California as the first to use the term "data-base" in a specific technical sense.
7050:
6851:
6806:
6624:
6405:
6150:
5664:
5649:
4850:
4138:
3815:
3699:
3645:
3614:
3354:
2488:
2383:
2040:
1995:
1554:
910:
869:
804:
614:
543:
396:
381:
354:
109:
101:
388:(often physical disk addresses) to follow relationships from one record to another.
6913:
6867:
6488:
6417:
6354:
6238:
5416:
4946:
4605:
2809:
2593:
2478:
2206:
1698:
1543:
992:
845:
711:
587:
448:
The next generation of post-relational databases in the late 2000s became known as
346:
306:
2336:
Another aspect of physical database design is security. It involves both defining
995:
are a type of structured document-oriented database that allows querying based on
665:
1861:
in the database architecture. It also contains all the information needed (e.g.,
1744:(DML) – performs tasks such as inserting, updating, or deleting data occurrences;
764:' Set-Theoretic Data model. MICRO was used to manage very large data sets by the
6964:
6928:
6690:
6558:
6287:
6029:
5654:
5634:
4936:
4562:
4474:
3837:
2493:
2427:
1898:
was used to store data, so multiple encodings can be used in the same database.
1887:
1722:
1627:
1452:
1300:
1216:
1193:
1166:
1153:
One way to classify databases involves the type of their contents, for example:
1057:
1018:
926:
715:
686:
being replaced by data held in multiple tables, connected only by logical keys.
642:
634:
345:. The concept of a database was made possible by the emergence of direct access
318:
206:
93:
3794:
3655:
Database
Systems – A Practical Approach to Design Implementation and Management
2588:
Database technology has been an active research topic since the 1960s, both in
37:
6974:
6877:
6660:
6655:
6548:
6393:
6166:
5798:
5707:
5669:
5644:
5453:
5115:
4956:
4886:
4479:
4212:
4068:
3777:
3435:
3387:
2709:
2605:
2463:
2354:
2220:
1804:
1686:
1678:
1623:
1516:
1326:
1311:
884:
880:
843:
IBM started working on a prototype system loosely based on Codd's concepts as
606:
databases are classified as network databases. IMS remains in use as of 2014.
583:
369:
62:
17:
3726:
3718:
3346:
1795:
is a standard XML query language implemented by XML database systems such as
7005:
6820:
6813:
6715:
6553:
6507:
6297:
6140:
6075:
5401:
4461:
4422:
3992:
3749:
3152:
Argumentation in
Artificial Intelligence by Iyad Rahwan, Guillermo R. Simari
2704:
2601:
1796:
1583:
Enforcing constraints to ensure data in the database abides by certain rules
1365:
1330:
1322:
1212:
891:
734:
622:
50:
1750:(DQL) – allows searching for information and computing derived information.
3637:
3497:
3480:
1781:). It has influenced the design of some of the newer query languages like
1413:
The major parallel DBMS architectures which are induced by the underlying
7015:
6705:
6512:
6135:
6070:
5659:
2589:
2551:
to enhance performance. Occasionally it stores data of individual views (
2278:
1862:
1360:, providing the means for the computerized collection, organization, and
1197:
898:. In 1984, this project was consolidated into an independent enterprise.
808:
746:
183:
78:
74:
2517:
A database management system provides three views of the database data:
1406:
for tasks such as loading data, building indexes and evaluating queries.
7025:
7020:
6792:
6785:
6720:
3337:
3320:
2729:
2266:, often with the aid of drawing tools. Another popular approach is the
1810:
1710:
1512:
1439:, where each processing unit has its own main memory and other storage.
1142:
1126:
863:
832:
828:
742:
524:
483:
412:
377:
241:
Both a database and its DBMS conform to the principles of a particular
3584:
Chong, Raul F.; Wang, Xiaomei; Dang, Michael; Snow, Dwaine R. (2007).
3300:
Ramalho, J.C.; Faria, L.; Helder, S.; Coutada, M. (31 December 2013).
2941:
701:
Codd's paper was picked up by two people at
Berkeley, Eugene Wong and
6938:
6841:
5564:
2647:
2592:
and in the research and development groups of companies (for example
2234:
2175:
1998:
and do not remove this message until the contradictions are resolved.
1814:
1792:
1786:
1036:
987:
706:
561:
461:
404:
314:
3901:
2218:– Performs query optimization on every query to choose an efficient
542:
Use of a primary key (known as a CALC key, typically implemented by
478:
205:
is often used to refer to any collection of related data (such as a
4005:
2433:
An object–relational database combines the two related structures.
1237:
is one in which both the data and the DBMS span multiple computers.
7010:
7000:
6918:
6897:
6670:
6110:
6105:
6100:
5944:
5559:
3986:
3055:
MICRO Information
Management System (Version 5.0) Reference Manual
2508:
2353:
2273:
Producing the conceptual data model sometimes involves input from
2250:
1800:
1647:
1534:
The DBMS acronym is sometimes extended to indicate the underlying
1508:
1003:
983:
930:
664:
528:
477:
449:
420:
167:
36:
2923:
1377:
can be carried on or synchronized from a mobile computing device.
925:. The new computers empowered their users with spreadsheets like
818:
Another approach to hardware support for database management was
6969:
6959:
6933:
6753:
5619:
2739:
2659:
2617:
2571:
The three-level database architecture relates to the concept of
2363:
2096:
1706:
1702:
1630:
with the database only directly connected to the adjacent tier.
726:
725:
IBM itself did one test implementation of the relational model,
527:, the group responsible for the creation and standardization of
428:
108:
spans formal techniques and practical considerations, including
6461:
6457:
6375:
6259:
5986:
5948:
5457:
5029:
4009:
3996:
2474:
Specialized models are optimized for particular types of data:
1574:
Facilities for recovering the database should it become damaged
6846:
3757:
Nelson, Anne
Fulcher; Nelson, William Harris Morehead (2001).
2576:
the impact of making physical changes to improve performance.
1971:
1701:
or a bridging API. Some API's aim to be database independent,
1642:
1476:
1051:
996:
571:
565:
317:), and their internal engineering, which affects performance,
298:
163:
42:
3759:
Building
Electronic Commerce: With Web Database Constructions
756:
In 1970, the
University of Michigan began development of the
437:
were developed in the 1980s to overcome the inconvenience of
3973:
2209:– This helps in keeping a history of the executed functions.
5025:
3368:
David Y. Chan; Victoria Chiu; Miklos A. Vasarhelyi (2018).
2690:
Comparison of object–relational database management systems
2302:
are often used interchangeably, but in this article we use
2099:
describes some ideal properties of a database transaction:
1705:
being a commonly known example. Other common API's include
714:
in a number of ways, including the use of a "language" for
225:– Insertion, modification, and deletion of the data itself.
3917:
887:, as do many large companies and financial institutions).
142:
may classify database management systems according to the
1825:
DBMS-specific configuration and storage engine management
1685:
interactions to the database (sometimes referred to as a
1337:, where users can conveniently jump around the text. The
850:
customers in 1978 and 1979, by which time a standardized
578:(IMS). IMS was a development of software written for the
3619:"A Relational Model of Data for Large Shared Data Banks"
3455:
3453:
3437:
Integration Definition for Information Modeling (IDEFIX)
3052:
M.A. Kahn; D.L. Rumelhart; B.L. Bronson (October 1977).
2310:
for the modeling notation used to express that design).
1821:
A database language may also incorporate features like:
1268:), and provides them with an integrated conceptual view.
749:
and Rel. Most other DBMS implementations usually called
722:. Over time, INGRES moved to the emerging SQL standard.
3321:"Opportunities of collected city data for smart cities"
1318:
such as satellite images and climate simulation output.
279:
support, but modern DBMSs typically rely on a standard
5070:
3793:
Tsitchizris, Dionysios C.; Lochovsky, Fred H. (1982).
2564:
department. Thus different departments need different
2258:
The first task of a database designer is to produce a
1577:
Support for authorization of access and update of data
628:
A Relational Model of Data for Large Shared Data Banks
3989: – information about files with the DB extension
3737:
A set theoretic data structure and retrieval language
3700:"Abstract Interpretation of Database Query Languages"
3143:
magazine, January 2007. Retrieved on August 13, 2008.
1600:
the need to target zero-administration is paramount.
2874:
2695:
Comparison of relational database management systems
6993:
6952:
6906:
6860:
6746:
6739:
6638:
6572:
6541:
6495:
6426:
6386:
6337:
6311:
6270:
6211:
6185:
6159:
6124:
6058:
5997:
5838:
5807:
5751:
5678:
5607:
5491:
5374:
5326:
5283:
5262:
5219:
5186:
5151:
5063:
4874:
4821:
4783:
4730:
4692:
4654:
4596:
4513:
4459:
4421:
4366:
4303:
4236:
4200:
4157:
4121:
4054:
3270:. International Business Machines. October 27, 2006
1947:
Replication (computing) § Database replication
1588:application interface sometimes referred to as the
411:applications, and as of 2018 they remain dominant:
3676:
3590:Understanding DB2: Learning Visually with Examples
2369:Common logical data models for databases include:
191:ways to manage how that information is organized.
150:became dominant in the 1980s. These model data as
3882:, 1st edition, Morgan Kaufmann Publishers, 1992.
3372:(1st ed.). Bingley, UK: Emerald Publishing.
3370:Continuous auditing : theory and application
3218:
2623:The database research area has several dedicated
399:, departed from this tradition by insisting that
2685:Comparison of object database management systems
788:. The system remained in production until 1998.
313:(s) used to access the database (such as SQL or
3925:Lightstone, S.; Teorey, T.; Nadeau, T. (2007).
3880:Transaction Processing: Concepts and Techniques
3003:
1777:is an object model language standard (from the
1341:is thus a large distributed hypertext database.
301:), the type(s) of computer they run on (from a
3945:Database Modeling & Design: Logical Design
3740:. Spring Joint Computer Conference, May 1972.
3653:Connolly, Thomas M.; Begg, Carolyn E. (2014).
3415:"How Database Administration Fits into DevOps"
3103:. The FoxPro History. Retrieved on 2013-07-12.
1769:International Organization for Standardization
784:. It ran on IBM mainframe computers using the
556:Scanning all the records in a sequential order
6473:
6439:Data warehousing products and their producers
5960:
5469:
5041:
4045:Note: This template roughly follows the 2012
4021:
3556:Description of a set-theoretic data structure
3400:
2886:
1207:converted from internal product codes to use
1044:guarantees of a traditional database system.
745:, and now there are two new implementations:
112:, efficient data representation and storage,
8:
3967:MIT OCW 6.830 | Fall 2010 | Database Systems
3947:, 4th edition, Morgan Kaufmann Press, 2005.
3707:Computer Languages, Systems & Structures
3242:
3230:
3206:
3194:
3182:
2898:
905:, emerged in 1976 and gained popularity for
3744:. Vol. 7, no. 4. pp. 45–55.
2796:
2306:for the design of a specific database, and
1633:A general-purpose DBMS will provide public
1086:. Unsourced material may be challenged and
6743:
6480:
6466:
6458:
6383:
6372:
6267:
6256:
5994:
5983:
5967:
5953:
5945:
5476:
5462:
5454:
5048:
5034:
5026:
4028:
4014:
4006:
3993:
3943:Teorey, T.; Lightstone, S. and Nadeau, T.
3734:Hershey, William; Easthope, Carol (1972).
2608:, the atomic transaction concept, related
1145:as collections of webpages in a database.
974:(ORMs) attempt to solve the same problem.
890:In Sweden, Codd's paper was also read and
662:foundations on which the model was based.
384:). These were characterized by the use of
3814:Ullman, Jeffrey; Widom, Jennifer (1997).
3778:"Sets, Data Models and Data Independence"
3496:
3336:
2854:"Administration Definition & Meaning"
1761:the relational model as described by Codd
1106:Learn how and when to remove this message
460:. A competing "next generation" known as
27:Organized collection of data in computing
3698:Halder, Raju; Cortesi, Agostino (2011).
2604:. Notable research topics have included
2505:External, conceptual, and internal views
2358:Collage of five types of database models
2125:Data migration § Database migration
1977:
1571:Support for transactions and concurrency
1490:, often customized for a specific field.
1356:or Δ) is a special kind of database for
1165:is a database that primarily resides in
957:and not to individual fields. The term "
574:also had its own DBMS in 1966, known as
5152:
3592:(2nd ed.). IBM Press Pearson plc.
3254:
3039:
3027:
2910:
2789:
2770:
2076:can be used to introduce some level of
1455:to draw inferences from imprecise data.
264:. DBMSs are found at the heart of most
6686:Knowledge representation and reasoning
6620:Semantic service-oriented architecture
4745:Knowledge representation and reasoning
3287:
1865:, "data about the data", and internal
1694:
1295:is a kind of NoSQL database that uses
96:, while large databases are hosted on
4770:Philosophy of artificial intelligence
3885:Kroenke, David M. and David J. Auer.
3788:from the original on 24 October 2012.
3537:from the original on 22 February 2009
3306:Biblioteca Nacional de Portugal (BNP)
3130:"COTS Databases For Embedded Systems"
3015:
1932:, which consist of frequently needed
1765:American National Standards Institute
1637:(API) and optionally a processor for
1402:seeks to improve performance through
268:. DBMSs may be built around a custom
7:
4089:Energy consumption (Green computing)
3510:(3rd ed.). Palgrave Macmillan.
3459:
2991:
2948:. Oxford University Press. June 2013
2832:"Retrieval Definition & Meaning"
2630:ACM Transactions on Database Systems
1894:Some DBMSs support specifying which
1610:or terminal emulation software. The
1580:Access support from remote locations
1084:adding citations to reliable sources
959:object–relational impedance mismatch
872:'s Oracle Database (or more simply,
770:U.S. Environmental Protection Agency
439:object–relational impedance mismatch
256:computers, with generous memory and
5929:
5429:
4775:Distributed artificial intelligence
4047:ACM Computing Classification System
3863:and Tamer M. Ă–zsu (Eds.) (2009). "
3679:An Introduction to Database Systems
2202:Other DBMS features might include:
1288:across the participating databases.
758:MICRO Information Management System
286:Since DBMSs comprise a significant
262:transaction processing environments
92:Small databases can be stored on a
6747:Syntax and supporting technologies
6324:MultiDimensional eXpressions (MDX)
4280:Integrated development environment
3817:A First Course in Database Systems
3070:"Oracle 30th Anniversary Timeline"
2842:from the original on Jun 27, 2023.
2820:from the original on Feb 25, 2024.
2406:Enhanced entity–relationship model
2329:. A key goal during this stage is
1987:appears to contradict the article
1635:application programming interfaces
1626:with the end user interface via a
1561:Data storage, retrieval and update
1211:so that they can be compared with
894:was developed in the mid-1970s at
705:. They started a project known as
515:, author of one such product, the
197:Outside the world of professional
25:
4755:Automated planning and scheduling
4285:Software configuration management
3889:3rd ed. New York: Prentice, 2007.
3268:"Structured Query Language (SQL)"
2864:from the original on Dec 6, 2023.
2810:"Update Definition & Meaning"
2139:Building, maintaining, and tuning
1286:distributed (global) transactions
549:Navigating relationships (called
5928:
5918:
5909:
5908:
5439:
5438:
5428:
5009:
4999:
4990:
4989:
3865:Encyclopedia of Database Systems
3413:Ben Linders (January 28, 2016).
2970:IBM Corporation (October 2013).
2875:Tsitchizris & Lochovsky 1982
2612:techniques, query languages and
1976:
1732:(DCL) – controls access to data;
1056:
945:The 1990s, along with a rise in
921:The 1980s ushered in the age of
594:. IMS is classified by IBM as a
482:Basic structure of navigational
368:The two main early navigational
5919:
5000:
4403:Computational complexity theory
3082:from the original on 2011-03-20
45:select statement and its result
6345:Business intelligence software
6224:Extract, load, transform (ELT)
6219:Extract, transform, load (ETL)
4187:Network performance evaluation
2755:Journal of Database Management
2636:Data and Knowledge Engineering
2596:). Research activity includes
680:first-order predicate calculus
505:System Development Corporation
57:is an organized collection of
1:
6861:Schemas, ontologies and rules
6293:Decision support system (DSS)
5382:Database-centric architecture
4558:Multimedia information system
4543:Geographic information system
4533:Enterprise information system
4122:Computer systems organization
3960:CMU Database courses playlist
3481:"The Programmer as Navigator"
2725:Database-centric architecture
1691:application program interface
1673:Application program interface
1484:terminology-oriented database
1266:heterogeneous database system
576:Information Management System
490:The introduction of the term
170:, because they use different
128:issues, including supporting
6319:Data Mining Extensions (DMX)
4917:Computational social science
4505:Theoretical computer science
4318:Software development process
4094:Electronic design automation
4079:Very Large Scale Integration
3776:North, Ken (10 March 2010).
3506:Beynon-Davies, Paul (2003).
3101:Interview with Wayne Ratliff
2680:Comparison of database tools
2423:Entity–attribute–value model
2063:Transactions and concurrency
1779:Object Data Management Group
1393:enterprise resource planning
553:) from one record to another
452:databases, introducing fast
395:, first proposed in 1970 by
321:, resilience, and security.
283:to provide these functions.
162:, and the vast majority use
7057:Database management systems
6080:Ensemble modeling patterns
6050:Single version of the truth
5485:Database management systems
4740:Natural language processing
4528:Information storage systems
3902:Database Management Systems
3004:Hershey & Easthope 1972
2568:of the company's database.
2379:Hierarchical database model
1903:database storage structures
1767:(ANSI) in 1986, and of the
1564:User accessible catalog or
1436:Shared-nothing architecture
1230:with a relational database.
967:object–relational databases
947:object-oriented programming
929:and database software like
772:, and researchers from the
592:The Programmer as Navigator
503:cites a 1962 report by the
458:document-oriented databases
443:object–relational databases
7078:
6888:Semantic Web Rule Language
6434:Comparison of OLAP servers
5891:Object–relational database
5397:Locks with ordered sharing
5229:Entities and relationships
5086:Database management system
4656:Human–computer interaction
4626:Intrusion detection system
4538:Social information systems
4523:Database management system
2924:"TOPDB Top Database index"
2669:
2347:
2244:
2173:
2142:
2122:
2066:
2014:
1944:
1921:
1842:
1742:Data manipulation language
1658:
1612:client–server architecture
1503:Database management system
1422:Shared memory architecture
1242:document-oriented database
1139:content management systems
1131:flight reservation systems
1025:to simultaneously provide
1010:data, and are designed to
981:
972:object–relational mappings
795:
471:
67:database management system
29:
6382:
6371:
6303:Data warehouse automation
6266:
6255:
5993:
5988:Creating a data warehouse
5982:
5904:
5866:Federated database system
5599:Blockchain-based database
5425:
5275:Object–relational mapping
4985:
4922:Computational engineering
4897:Computational mathematics
4043:
4003:
3998:Links to related articles
3929:. Morgan Kaufmann Press.
3867:, 4100 p. 60 illus.
3683:(8th ed.). Pearson.
3657:(6th ed.). Pearson.
3626:Communications of the ACM
3485:Communications of the ACM
3401:Halder & Cortesi 2011
3141:Embedded Computing Design
2670:For a topical guide, see
2401:Entity–relationship model
2268:Unified Modeling Language
2264:entity–relationship model
1282:two-phase commit protocol
1261:federated database system
1021:, it is impossible for a
903:entity–relationship model
733:, both now discontinued.
501:Oxford English Dictionary
6994:Microformat vocabularies
6666:Information architecture
4932:Computational healthcare
4927:Differentiable computing
4846:Graphics processing unit
4265:Domain-specific language
4134:Computational complexity
3918:Database System Concepts
3878:Gray, J. and Reuter, A.
3835:Wagner, Michael (2010),
3719:10.1016/j.cl.2011.10.004
3243:Connolly & Begg 2014
3231:Connolly & Begg 2014
3207:Connolly & Begg 2014
3195:Connolly & Begg 2014
3183:Connolly & Begg 2014
2959:(Subscription required.)
2899:Nelson & Nelson 2001
2759:Question-focused dataset
2513:Traditional view of data
2325:, and the output is the
2323:physical database design
2132:total costs of ownership
1736:Data definition language
1488:object-oriented database
1429:Shared disk architecture
901:Another data model, the
807:, the early offering of
786:Michigan Terminal System
753:are actually SQL DBMSs.
729:, and a production one,
468:1960s, navigational DBMS
178:Terminology and overview
6883:Rule Interchange Format
6646:Collective intelligence
6329:XML for Analysis (XMLA)
4907:Computational chemistry
4841:Photograph manipulation
4732:Artificial intelligence
4548:Decision support system
3750:10.1145/1095495.1095500
2797:Ullman & Widom 1997
2191:Abstract interpretation
1568:describing the metadata
1548:object–relational model
1449:Probabilistic databases
1135:parts inventory systems
978:2000s, NoSQL and NewSQL
365:, and post-relational.
124:of sensitive data, and
6261:Using a data warehouse
6116:Operational data store
5896:Transaction processing
5851:Database normalization
5794:Query rewriting system
4972:Educational technology
4803:Reinforcement learning
4553:Process control system
4451:Computational geometry
4441:Algorithmic efficiency
4436:Analysis of algorithms
4084:Systems on Chip (SoCs)
3525:Chapple, Mike (2005).
3308:. University of Minho.
2514:
2459:Multidimensional model
2454:Other models include:
2374:Navigational databases
2359:
2255:
2198:Miscellaneous features
2084:after recovery from a
1994:Please discuss at the
1616:multitier architecture
941:1990s, object-oriented
782:Wayne State University
778:University of Michigan
766:US Department of Labor
674:
610:1970s, relational DBMS
487:
427:are the most searched
199:information technology
65:based on the use of a
46:
6278:Business intelligence
5871:Referential integrity
5176:information retrieval
4942:Electronic publishing
4912:Computational biology
4902:Computational physics
4798:Unsupervised learning
4712:Distributed computing
4588:Information retrieval
4495:Mathematical analysis
4485:Mathematical software
4368:Theory of computation
4333:Software construction
4323:Requirements analysis
4201:Software organization
4129:Computer architecture
4099:Hardware acceleration
4064:Printed circuit board
3638:10.1145/362384.362685
3586:"Introduction to DB2"
3498:10.1145/355611.362534
2512:
2357:
2277:, or the analysis of
2260:conceptual data model
2254:
2074:Database transactions
2067:Further information:
1912:correlation databases
1869:) to reconstruct the
1845:Computer data storage
1730:Data control language
1538:, with RDBMS for the
1381:Operational databases
917:1980s, on the desktop
774:University of Alberta
668:
596:hierarchical database
517:Integrated Data Store
481:
474:Navigational database
472:Further information:
266:database applications
248:Physically, database
126:distributed computing
40:
6681:Knowledge management
6676:Knowledge extraction
6094:Focal point modeling
6066:Column-oriented DBMS
6015:Dimensional modeling
5861:Distributed database
5387:Intelligent database
4702:Concurrent computing
4674:Ubiquitous computing
4646:Application security
4641:Information security
4470:Discrete mathematics
4446:Randomized algorithm
4398:Computability theory
4376:Model of computation
4348:Software maintenance
4343:Software engineering
4305:Software development
4255:Programming language
4250:Programming paradigm
4167:Network architecture
3909:Abraham Silberschatz
3839:, Diplomica Verlag,
3434:itl.nist.gov (1993)
2672:Outline of databases
2437:Physical data models
1661:Database application
1521:Microsoft SQL Server
1358:knowledge management
1335:online encyclopedias
1235:distributed database
1080:improve this section
1031:eventual consistency
839:Late 1970s, SQL DBMS
619:San Jose, California
560:Later systems added
425:Microsoft SQL Server
148:Relational databases
77:that interacts with
6953:Common vocabularies
6907:Semantic annotation
6605:Semantic publishing
6399:Information factory
6172:Early-arriving fact
6089:Data vault modeling
6040:Reverse star schema
5881:Relational calculus
5759:Concurrency control
5196:Activity monitoring
4977:Document management
4967:Operations research
4892:Enterprise software
4808:Multi-task learning
4793:Supervised learning
4515:Information systems
4338:Software deployment
4295:Software repository
4149:Real-time computing
3477:Bachman, Charles W.
3447:. 21 December 1993.
3233:, pp. 106–113.
2610:concurrency control
2600:and development of
2327:physical data model
2241:Design and modeling
2069:Concurrency control
1962:data virtualization
1748:Data query language
1620:application servers
1546:and ORDBMS for the
1459:Real-time databases
1387:. Examples include
1271:Sometimes the term
1120:Enterprise software
792:Integrated approach
703:Michael Stonebraker
648:relational calculus
521:Database Task Group
519:(IDS), founded the
146:that they support.
140:Computer scientists
106:design of databases
6701:Digital humanities
6590:Semantic computing
6580:Semantic analytics
6564:Rule-based systems
6350:Reporting software
5876:Relational algebra
5820:Query optimization
5625:Armstrong's axioms
5366:Online real estate
4760:Search methodology
4707:Parallel computing
4664:Interaction design
4573:Computing platform
4500:Numerical analysis
4490:Information theory
4275:Software framework
4238:Software notations
4177:Network components
4074:Integrated circuit
3893:Raghu Ramakrishnan
3887:Database Concepts.
3527:"SQL Fundamentals"
3443:2013-12-03 at the
3338:10.1049/smc2.12044
3197:, pp. 97–102.
3163:"OWL DL Semantics"
3135:2007-11-14 at the
2887:Beynon-Davies 2003
2745:Flat-file database
2614:query optimization
2553:materialized views
2515:
2360:
2291:logical data model
2275:business processes
2256:
2170:Backup and restore
1930:materialized views
1918:Materialized views
1901:Various low-level
1896:character encoding
1717:Database languages
1639:database languages
1598:embedded databases
1417:architecture are:
1389:customer databases
1224:deductive database
1163:in-memory database
1023:distributed system
1012:scale horizontally
896:Uppsala University
815:database machine.
731:Business System 12
675:
488:
374:hierarchical model
47:
32:Lists of databases
7044:
7043:
7038:
7037:
7034:
7033:
6944:Facebook Platform
6831:
6830:(no W3C standard)
6823:
6816:
6809:
6802:
6795:
6788:
6781:
6767:
6731:Web Science Trust
6651:Description logic
6610:Semantic reasoner
6600:Semantic matching
6528:Semantic networks
6455:
6454:
6451:
6450:
6447:
6446:
6367:
6366:
6363:
6362:
6251:
6250:
6247:
6246:
6146:Sixth normal form
5942:
5941:
5550:Wide-column store
5545:Document-oriented
5451:
5450:
5412:Halloween Problem
5392:Two-phase locking
5351:Facial expression
5270:Abstraction layer
5211:Negative database
5166:Data manipulation
5023:
5022:
4952:Electronic voting
4882:Quantum Computing
4875:Applied computing
4861:Image compression
4631:Hardware security
4621:Security services
4578:Digital marketing
4358:Open-source model
4270:Modeling language
4182:Network scheduler
3987:DB File extension
3936:978-0-12-369389-1
3873:978-0-387-49616-0
3820:. Prentice–Hall.
3799:. Prentice–Hall.
3761:. Prentice Hall.
3462:, pp. 31–32.
3379:978-1-78743-413-4
3219:Chong et al. 2007
2639:-DKE) and annual
2625:academic journals
2573:data independence
2499:Time series model
2331:data independence
2045:physical security
2022:Database security
2017:Database security
2013:
2012:
1989:Database security
1924:Materialized view
1695:database language
1544:object (oriented)
1542:, OODBMS for the
1495:unstructured data
1473:temporal database
1400:parallel database
1305:network databases
1249:embedded database
1228:logic programming
1179:database triggers
1116:
1115:
1108:
923:desktop computing
813:Britton Lee, Inc.
617:worked at IBM in
343:computer networks
184:computer software
98:computer clusters
16:(Redirected from
7069:
6826:
6819:
6812:
6805:
6798:
6791:
6784:
6777:
6763:
6744:
6482:
6475:
6468:
6459:
6384:
6373:
6268:
6257:
6035:Snowflake schema
5995:
5984:
5969:
5962:
5955:
5946:
5932:
5931:
5922:
5921:
5912:
5911:
5886:Relational model
5856:Database storage
5733:Stored procedure
5478:
5471:
5464:
5455:
5442:
5441:
5432:
5431:
5050:
5043:
5036:
5027:
5013:
5012:
5003:
5002:
4993:
4992:
4813:Cross-validation
4785:Machine learning
4669:Social computing
4636:Network security
4431:Algorithm design
4353:Programming team
4313:Control variable
4290:Software library
4228:Software quality
4223:Operating system
4172:Network protocol
4037:Computer science
4030:
4023:
4016:
4007:
3994:
3974:Berkeley CS W186
3940:
3915:, S. Sudarshan,
3849:
3831:
3810:
3789:
3772:
3753:
3730:
3704:
3694:
3682:
3668:
3649:
3623:
3610:
3608:
3606:
3580:
3578:
3568:Childs, David L.
3563:
3561:
3551:Childs, David L.
3546:
3544:
3542:
3521:
3508:Database Systems
3502:
3500:
3463:
3457:
3448:
3432:
3426:
3425:
3423:
3421:
3410:
3404:
3398:
3392:
3391:
3365:
3359:
3358:
3340:
3325:IET Smart Cities
3316:
3310:
3309:
3297:
3291:
3285:
3279:
3278:
3276:
3275:
3264:
3258:
3252:
3246:
3240:
3234:
3228:
3222:
3216:
3210:
3204:
3198:
3192:
3186:
3180:
3174:
3173:
3171:
3169:
3159:
3153:
3150:
3144:
3126:
3120:
3110:
3104:
3098:
3092:
3091:
3089:
3087:
3081:
3074:
3066:
3060:
3059:
3049:
3043:
3037:
3031:
3025:
3019:
3013:
3007:
3001:
2995:
2989:
2983:
2982:
2980:
2978:
2967:
2961:
2960:
2957:
2955:
2953:
2938:
2932:
2931:
2920:
2914:
2908:
2902:
2896:
2890:
2884:
2878:
2872:
2866:
2865:
2850:
2844:
2843:
2828:
2822:
2821:
2806:
2800:
2794:
2778:
2775:
2720:Database testing
2530:conceptual level
2469:Multivalue model
2396:Relational model
2008:
2005:
1999:
1980:
1979:
1972:
1871:conceptual level
1529:Microsoft Access
1466:spatial database
1297:graph structures
1190:cloud technology
1111:
1104:
1100:
1097:
1091:
1060:
1052:
963:Object databases
935:C. Wayne Ratliff
798:Database machine
747:Alphora Dataphor
671:relational model
533:CODASYL approach
497:batch processing
454:key–value stores
435:Object databases
393:relational model
339:computer storage
281:operating system
21:
7077:
7076:
7072:
7071:
7070:
7068:
7067:
7066:
7047:
7046:
7045:
7040:
7039:
7030:
6989:
6948:
6902:
6856:
6735:
6726:Web engineering
6696:Digital library
6634:
6615:Semantic search
6595:Semantic mapper
6585:Semantic broker
6568:
6537:
6491:
6486:
6456:
6443:
6422:
6378:
6359:
6333:
6307:
6262:
6243:
6207:
6203:Slowly changing
6193:Dimension table
6181:
6155:
6132:Data dictionary
6120:
6084:Anchor modeling
6054:
5989:
5978:
5976:Data warehouses
5973:
5943:
5938:
5900:
5846:Database models
5834:
5803:
5789:Query optimizer
5764:Data dictionary
5747:
5718:Transaction log
5674:
5630:Codd's 12 rules
5603:
5533:Column-oriented
5499:Object-oriented
5487:
5482:
5452:
5447:
5421:
5370:
5322:
5279:
5258:
5215:
5182:
5161:Data definition
5147:
5059:
5054:
5024:
5019:
5010:
4981:
4962:Word processing
4870:
4856:Virtual reality
4817:
4779:
4750:Computer vision
4726:
4722:Multiprocessing
4688:
4650:
4616:Security hacker
4592:
4568:Digital library
4509:
4460:Mathematics of
4455:
4417:
4393:Automata theory
4388:Formal language
4362:
4328:Software design
4299:
4232:
4218:Virtual machine
4196:
4192:Network service
4153:
4144:Embedded system
4117:
4050:
4039:
4034:
3999:
3983:
3937:
3924:
3897:Johannes Gehrke
3857:
3855:Further reading
3852:
3847:
3834:
3828:
3813:
3807:
3792:
3775:
3769:
3756:
3742:ACM SIGIR Forum
3733:
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3491:(11): 653–658.
3475:
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3137:Wayback Machine
3128:Graves, Steve.
3127:
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2858:Merriam-Webster
2852:
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2836:Merriam-Webster
2830:
2829:
2825:
2814:Merriam-Webster
2808:
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2803:
2795:
2791:
2787:
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2776:
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2767:
2762:
2735:Database-as-IPC
2715:Database theory
2675:
2668:
2586:
2562:human resources
2507:
2352:
2346:
2249:
2247:Database design
2243:
2237:for database".
2216:Query optimizer
2200:
2187:
2185:Static analysis
2178:
2172:
2152:user interfaces
2147:
2145:Database tuning
2141:
2127:
2121:
2078:fault tolerance
2071:
2065:
2049:data encryption
2019:
2009:
2003:
2000:
1993:
1981:
1970:
1958:
1949:
1943:
1926:
1920:
1908:column-oriented
1884:database engine
1867:data structures
1851:
1849:Database engine
1843:Main articles:
1841:
1719:
1693:(API) or via a
1675:
1663:
1657:
1590:database engine
1566:data dictionary
1525:Oracle Database
1505:
1486:builds upon an
1404:parallelization
1375:mobile database
1204:Data warehouses
1174:active database
1151:
1133:, computerized
1112:
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982:Main articles:
980:
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907:database design
841:
800:
794:
612:
513:Charles Bachman
476:
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409:data processing
335:computer memory
327:
217:Data definition
180:
172:query languages
158:in a series of
144:database models
134:fault tolerance
114:query languages
87:database system
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4611:Formal methods
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4583:World Wide Web
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4000:
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3990:
3982:
3981:External links
3979:
3978:
3977:
3970:
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3956:
3941:
3935:
3922:
3913:Henry F. Korth
3906:
3890:
3883:
3876:
3856:
3853:
3851:
3850:
3846:978-3836696098
3845:
3832:
3827:978-0138613372
3826:
3811:
3806:978-0131964280
3805:
3790:
3773:
3768:978-0201741308
3767:
3754:
3731:
3713:(2): 123–157.
3695:
3690:978-0321197849
3689:
3669:
3664:978-1292061184
3663:
3650:
3632:(6): 377–387.
3615:Codd, Edgar F.
3611:
3599:978-0131580183
3598:
3581:
3564:
3547:
3522:
3517:978-1403916013
3516:
3503:
3472:
3470:
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3427:
3405:
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3378:
3360:
3331:(4): 275–291.
3311:
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3259:
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3209:, p. 102.
3199:
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2928:pypl.github.io
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2750:INP (database)
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2700:Data hierarchy
2697:
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2664:
2627:(for example,
2585:
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2545:physical level
2541:internal level
2537:
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2523:external level
2506:
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2484:Semantic model
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2444:Inverted index
2431:
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2418:Document model
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2389:Graph database
2386:
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2350:Database model
2348:Main article:
2345:
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2338:access control
2308:database model
2300:database model
2245:Main article:
2242:
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2225:
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2210:
2199:
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2186:
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2174:Main article:
2171:
2168:
2143:Main article:
2140:
2137:
2120:
2117:
2082:data integrity
2064:
2061:
2056:database audit
2015:Main article:
2011:
2010:
1984:
1982:
1975:
1969:
1966:
1957:
1956:Virtualization
1954:
1942:
1939:
1934:external views
1922:Main article:
1919:
1916:
1875:external level
1840:
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1659:Main article:
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1346:knowledge base
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1339:World Wide Web
1319:
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1293:graph database
1289:
1273:multi-database
1269:
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1186:cloud database
1182:
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1149:Classification
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858:, and, later,
852:query language
840:
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796:Main article:
793:
790:
611:
608:
600:Cincom Systems
580:Apollo program
558:
557:
554:
547:
486:database model
469:
466:
351:magnetic disks
326:
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311:query language
303:server cluster
275:with built-in
254:multiprocessor
243:database model
239:
238:
235:Administration
232:
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18:Database query
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6625:Semantic wiki
6623:
6621:
6618:
6616:
6613:
6611:
6608:
6606:
6603:
6601:
6598:
6596:
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6516:
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6509:
6506:
6504:
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6498:
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6490:
6483:
6478:
6476:
6471:
6469:
6464:
6463:
6460:
6440:
6437:
6435:
6432:
6431:
6429:
6425:
6419:
6416:
6412:
6409:
6408:
6407:
6406:Ralph Kimball
6404:
6400:
6397:
6396:
6395:
6392:
6391:
6389:
6385:
6381:
6374:
6370:
6356:
6353:
6351:
6348:
6346:
6343:
6342:
6340:
6336:
6330:
6327:
6325:
6322:
6320:
6317:
6316:
6314:
6310:
6304:
6301:
6299:
6296:
6294:
6291:
6289:
6286:
6284:
6281:
6279:
6276:
6275:
6273:
6269:
6265:
6258:
6254:
6240:
6237:
6235:
6232:
6230:
6227:
6225:
6222:
6220:
6217:
6216:
6214:
6210:
6204:
6201:
6199:
6196:
6194:
6191:
6190:
6188:
6184:
6178:
6175:
6173:
6170:
6168:
6165:
6164:
6162:
6158:
6152:
6151:Surrogate key
6149:
6147:
6144:
6142:
6139:
6137:
6133:
6130:
6129:
6127:
6123:
6117:
6114:
6112:
6109:
6107:
6104:
6102:
6099:
6095:
6092:
6090:
6087:
6085:
6082:
6081:
6079:
6077:
6074:
6072:
6069:
6067:
6064:
6063:
6061:
6057:
6051:
6048:
6046:
6043:
6041:
6038:
6036:
6033:
6031:
6028:
6026:
6023:
6021:
6018:
6016:
6013:
6011:
6008:
6006:
6003:
6002:
6000:
5996:
5992:
5985:
5981:
5977:
5970:
5965:
5963:
5958:
5956:
5951:
5950:
5947:
5935:
5927:
5925:
5917:
5915:
5907:
5906:
5903:
5897:
5894:
5892:
5889:
5887:
5884:
5882:
5879:
5877:
5874:
5872:
5869:
5867:
5864:
5862:
5859:
5857:
5854:
5852:
5849:
5847:
5844:
5843:
5841:
5837:
5831:
5828:
5826:
5823:
5821:
5818:
5816:
5813:
5812:
5810:
5806:
5800:
5797:
5795:
5792:
5790:
5787:
5785:
5782:
5780:
5777:
5775:
5772:
5770:
5767:
5765:
5762:
5760:
5757:
5756:
5754:
5750:
5744:
5741:
5739:
5736:
5734:
5731:
5729:
5726:
5724:
5721:
5719:
5716:
5714:
5711:
5709:
5706:
5702:
5699:
5697:
5694:
5692:
5689:
5688:
5687:
5684:
5683:
5681:
5677:
5671:
5668:
5666:
5665:Surrogate key
5663:
5661:
5658:
5656:
5653:
5651:
5650:Candidate key
5648:
5646:
5643:
5641:
5638:
5636:
5633:
5631:
5628:
5626:
5623:
5621:
5618:
5616:
5613:
5612:
5610:
5606:
5600:
5597:
5595:
5592:
5588:
5585:
5584:
5583:
5580:
5576:
5573:
5572:
5571:
5568:
5566:
5563:
5561:
5558:
5556:
5553:
5551:
5548:
5546:
5543:
5539:
5536:
5535:
5534:
5531:
5529:
5526:
5522:
5519:
5517:
5514:
5513:
5512:
5509:
5505:
5502:
5501:
5500:
5497:
5496:
5494:
5490:
5486:
5479:
5474:
5472:
5467:
5465:
5460:
5459:
5456:
5446:
5445:
5436:
5435:
5424:
5418:
5415:
5413:
5410:
5408:
5405:
5403:
5400:
5398:
5395:
5393:
5390:
5388:
5385:
5383:
5380:
5379:
5377:
5373:
5367:
5364:
5362:
5359:
5357:
5354:
5352:
5349:
5347:
5344:
5342:
5339:
5337:
5334:
5333:
5331:
5329:
5325:
5319:
5316:
5314:
5311:
5309:
5306:
5302:
5299:
5298:
5297:
5294:
5292:
5289:
5288:
5286:
5282:
5276:
5273:
5271:
5268:
5267:
5265:
5261:
5255:
5252:
5250:
5247:
5245:
5242:
5240:
5239:Normalization
5237:
5234:
5230:
5227:
5226:
5224:
5222:
5218:
5212:
5209:
5207:
5204:
5202:
5199:
5197:
5194:
5193:
5191:
5189:
5185:
5177:
5174:
5173:
5172:
5169:
5167:
5164:
5162:
5159:
5158:
5156:
5154:
5150:
5144:
5141:
5139:
5136:
5134:
5131:
5129:
5128:Administrator
5126:
5122:
5119:
5117:
5114:
5113:
5112:
5109:
5107:
5104:
5102:
5099:
5097:
5094:
5092:
5089:
5087:
5084:
5082:
5079:
5077:
5074:
5072:
5069:
5068:
5066:
5062:
5058:
5051:
5046:
5044:
5039:
5037:
5032:
5031:
5028:
5016:
5008:
5006:
4998:
4996:
4988:
4987:
4984:
4978:
4975:
4973:
4970:
4968:
4965:
4963:
4960:
4958:
4955:
4953:
4950:
4948:
4945:
4943:
4940:
4938:
4935:
4933:
4930:
4928:
4925:
4923:
4920:
4918:
4915:
4913:
4910:
4908:
4905:
4903:
4900:
4898:
4895:
4893:
4890:
4888:
4885:
4883:
4880:
4879:
4877:
4873:
4867:
4864:
4862:
4859:
4857:
4854:
4852:
4851:Mixed reality
4849:
4847:
4844:
4842:
4839:
4837:
4834:
4832:
4829:
4828:
4826:
4824:
4820:
4814:
4811:
4809:
4806:
4804:
4801:
4799:
4796:
4794:
4791:
4790:
4788:
4786:
4782:
4776:
4773:
4771:
4768:
4766:
4763:
4761:
4758:
4756:
4753:
4751:
4748:
4746:
4743:
4741:
4738:
4737:
4735:
4733:
4729:
4723:
4720:
4718:
4715:
4713:
4710:
4708:
4705:
4703:
4700:
4699:
4697:
4695:
4691:
4685:
4684:Accessibility
4682:
4680:
4679:Visualization
4677:
4675:
4672:
4670:
4667:
4665:
4662:
4661:
4659:
4657:
4653:
4647:
4644:
4642:
4639:
4637:
4634:
4632:
4629:
4627:
4624:
4622:
4619:
4617:
4614:
4612:
4609:
4607:
4604:
4603:
4601:
4599:
4595:
4589:
4586:
4584:
4581:
4579:
4576:
4574:
4571:
4569:
4566:
4564:
4561:
4559:
4556:
4554:
4551:
4549:
4546:
4544:
4541:
4539:
4536:
4534:
4531:
4529:
4526:
4524:
4521:
4520:
4518:
4516:
4512:
4506:
4503:
4501:
4498:
4496:
4493:
4491:
4488:
4486:
4483:
4481:
4478:
4476:
4473:
4471:
4468:
4467:
4465:
4463:
4458:
4452:
4449:
4447:
4444:
4442:
4439:
4437:
4434:
4432:
4429:
4428:
4426:
4424:
4420:
4414:
4411:
4409:
4406:
4404:
4401:
4399:
4396:
4394:
4391:
4389:
4386:
4382:
4379:
4378:
4377:
4374:
4373:
4371:
4369:
4365:
4359:
4356:
4354:
4351:
4349:
4346:
4344:
4341:
4339:
4336:
4334:
4331:
4329:
4326:
4324:
4321:
4319:
4316:
4314:
4311:
4310:
4308:
4306:
4302:
4296:
4293:
4291:
4288:
4286:
4283:
4281:
4278:
4276:
4273:
4271:
4268:
4266:
4263:
4261:
4258:
4256:
4253:
4251:
4248:
4247:
4245:
4243:
4239:
4235:
4229:
4226:
4224:
4221:
4219:
4216:
4214:
4211:
4209:
4206:
4205:
4203:
4199:
4193:
4190:
4188:
4185:
4183:
4180:
4178:
4175:
4173:
4170:
4168:
4165:
4164:
4162:
4160:
4156:
4150:
4147:
4145:
4142:
4140:
4139:Dependability
4137:
4135:
4132:
4130:
4127:
4126:
4124:
4120:
4114:
4110:
4107:
4105:
4102:
4100:
4097:
4095:
4092:
4090:
4087:
4085:
4082:
4080:
4077:
4075:
4072:
4070:
4067:
4065:
4062:
4061:
4059:
4057:
4053:
4048:
4042:
4038:
4031:
4026:
4024:
4019:
4017:
4012:
4011:
4008:
4002:
3995:
3988:
3985:
3984:
3980:
3976:
3975:
3971:
3969:
3968:
3964:
3962:
3961:
3957:
3954:
3953:0-12-685352-5
3950:
3946:
3942:
3938:
3932:
3928:
3923:
3920:
3919:
3914:
3910:
3907:
3904:
3903:
3898:
3894:
3891:
3888:
3884:
3881:
3877:
3874:
3870:
3866:
3862:
3859:
3858:
3854:
3848:
3842:
3838:
3833:
3829:
3823:
3819:
3818:
3812:
3808:
3802:
3798:
3797:
3791:
3787:
3783:
3779:
3774:
3770:
3764:
3760:
3755:
3751:
3747:
3743:
3739:
3738:
3732:
3728:
3724:
3720:
3716:
3712:
3708:
3701:
3696:
3692:
3686:
3681:
3680:
3674:
3670:
3666:
3660:
3656:
3651:
3647:
3643:
3639:
3635:
3631:
3627:
3620:
3616:
3612:
3601:
3595:
3591:
3587:
3582:
3575:
3574:
3569:
3565:
3558:
3557:
3552:
3548:
3536:
3533:. About.com.
3532:
3528:
3523:
3519:
3513:
3509:
3504:
3499:
3494:
3490:
3486:
3482:
3478:
3474:
3473:
3468:
3461:
3456:
3454:
3450:
3446:
3442:
3439:
3438:
3431:
3428:
3416:
3409:
3406:
3402:
3397:
3394:
3389:
3385:
3381:
3375:
3371:
3364:
3361:
3356:
3352:
3348:
3344:
3339:
3334:
3330:
3326:
3322:
3315:
3312:
3307:
3303:
3296:
3293:
3289:
3284:
3281:
3269:
3263:
3260:
3256:
3251:
3248:
3245:, p. 65.
3244:
3239:
3236:
3232:
3227:
3224:
3220:
3215:
3212:
3208:
3203:
3200:
3196:
3191:
3188:
3185:, p. 64.
3184:
3179:
3176:
3164:
3158:
3155:
3149:
3146:
3142:
3138:
3134:
3131:
3125:
3122:
3119:
3118:0-89791-204-7
3115:
3109:
3106:
3102:
3097:
3094:
3078:
3071:
3065:
3062:
3057:
3056:
3048:
3045:
3041:
3036:
3033:
3029:
3024:
3021:
3017:
3012:
3009:
3005:
3000:
2997:
2993:
2988:
2985:
2973:
2966:
2963:
2947:
2943:
2942:"database, n"
2937:
2934:
2929:
2925:
2919:
2916:
2912:
2907:
2904:
2900:
2895:
2892:
2888:
2883:
2880:
2876:
2871:
2868:
2863:
2859:
2855:
2849:
2846:
2841:
2837:
2833:
2827:
2824:
2819:
2815:
2811:
2805:
2802:
2798:
2793:
2790:
2784:
2774:
2771:
2764:
2758:
2756:
2753:
2751:
2748:
2746:
2743:
2741:
2738:
2736:
2733:
2731:
2728:
2726:
2723:
2721:
2718:
2716:
2713:
2711:
2708:
2706:
2703:
2701:
2698:
2696:
2693:
2691:
2688:
2686:
2683:
2681:
2678:
2677:
2673:
2665:
2663:
2661:
2657:
2653:
2649:
2646:
2642:
2638:
2637:
2632:
2631:
2626:
2621:
2619:
2615:
2611:
2607:
2603:
2599:
2595:
2591:
2583:
2581:
2577:
2574:
2569:
2567:
2563:
2554:
2550:
2546:
2542:
2538:
2535:
2534:logical level
2531:
2527:
2524:
2520:
2519:
2518:
2511:
2504:
2500:
2497:
2495:
2492:
2490:
2489:Content store
2487:
2485:
2482:
2480:
2477:
2476:
2475:
2470:
2467:
2465:
2462:
2460:
2457:
2456:
2455:
2450:
2447:
2445:
2442:
2441:
2440:
2438:
2434:
2429:
2426:
2424:
2421:
2419:
2416:
2414:
2411:
2407:
2404:
2403:
2402:
2399:
2397:
2394:
2390:
2387:
2385:
2384:Network model
2382:
2380:
2377:
2376:
2375:
2372:
2371:
2370:
2367:
2365:
2356:
2351:
2343:
2341:
2339:
2334:
2332:
2328:
2324:
2319:
2317:
2316:normalization
2311:
2309:
2305:
2301:
2297:
2292:
2288:
2283:
2280:
2276:
2271:
2269:
2265:
2261:
2253:
2248:
2240:
2238:
2236:
2226:
2223:
2222:
2217:
2214:
2211:
2208:
2207:Database logs
2205:
2204:
2203:
2197:
2195:
2192:
2184:
2182:
2177:
2169:
2167:
2165:
2160:
2156:
2153:
2146:
2138:
2136:
2133:
2126:
2118:
2116:
2114:
2110:
2106:
2102:
2098:
2093:
2091:
2087:
2083:
2079:
2075:
2070:
2062:
2060:
2057:
2052:
2050:
2046:
2042:
2041:Data security
2038:
2035:
2030:
2026:
2023:
2018:
2007:
1997:
1991:
1990:
1985:This article
1983:
1974:
1973:
1967:
1965:
1963:
1955:
1953:
1948:
1940:
1938:
1935:
1931:
1925:
1917:
1915:
1913:
1909:
1904:
1899:
1897:
1892:
1889:
1885:
1881:
1876:
1872:
1868:
1864:
1860:
1856:
1850:
1846:
1838:
1833:
1830:
1827:
1824:
1823:
1822:
1816:
1812:
1809:
1806:
1802:
1798:
1794:
1791:
1788:
1784:
1780:
1776:
1773:
1770:
1766:
1762:
1757:
1756:
1755:
1749:
1746:
1743:
1740:
1737:
1734:
1731:
1728:
1727:
1726:
1724:
1716:
1714:
1712:
1708:
1704:
1700:
1696:
1692:
1688:
1684:
1680:
1672:
1670:
1668:
1667:database tool
1662:
1654:
1652:
1649:
1644:
1640:
1636:
1631:
1629:
1625:
1621:
1617:
1613:
1609:
1604:
1601:
1599:
1593:
1591:
1582:
1579:
1576:
1573:
1570:
1567:
1563:
1560:
1559:
1558:
1556:
1551:
1549:
1545:
1541:
1537:
1532:
1530:
1526:
1522:
1518:
1514:
1510:
1502:
1496:
1492:
1489:
1485:
1481:
1478:
1474:
1470:
1467:
1463:
1460:
1457:
1454:
1450:
1447:
1446:
1438:
1437:
1433:
1430:
1427:
1424:
1423:
1419:
1418:
1416:
1412:
1411:
1410:
1409:
1405:
1401:
1397:
1394:
1390:
1386:
1382:
1379:
1376:
1372:
1371:
1367:
1363:
1359:
1355:
1351:
1348:(abbreviated
1347:
1343:
1340:
1336:
1332:
1328:
1324:
1320:
1317:
1313:
1309:
1306:
1302:
1298:
1294:
1290:
1287:
1283:
1279:
1274:
1270:
1267:
1262:
1258:
1254:
1250:
1246:
1243:
1239:
1236:
1232:
1229:
1225:
1221:
1218:
1214:
1210:
1205:
1202:
1199:
1195:
1191:
1187:
1183:
1180:
1175:
1171:
1168:
1164:
1160:
1159:
1158:
1156:
1155:bibliographic
1148:
1146:
1144:
1140:
1136:
1132:
1128:
1123:
1121:
1110:
1107:
1099:
1089:
1085:
1081:
1075:
1074:
1070:
1065:This section
1063:
1059:
1054:
1053:
1047:
1045:
1043:
1038:
1034:
1032:
1028:
1024:
1020:
1015:
1013:
1009:
1005:
1001:
998:
994:
993:XML databases
989:
985:
977:
975:
973:
968:
964:
960:
956:
952:
948:
940:
938:
936:
932:
928:
924:
916:
914:
912:
911:data modeling
908:
904:
899:
897:
893:
888:
886:
882:
877:
875:
871:
870:Larry Ellison
867:
865:
861:
857:
853:
848:
847:
838:
836:
834:
830:
825:
821:
816:
814:
810:
806:
805:IBM System/38
799:
791:
789:
787:
783:
779:
775:
771:
767:
763:
759:
754:
752:
748:
744:
740:
736:
732:
728:
723:
721:
717:
713:
708:
704:
699:
695:
693:
687:
683:
681:
672:
667:
663:
659:
657:
653:
649:
644:
640:
636:
631:
629:
624:
620:
616:
615:Edgar F. Codd
609:
607:
605:
601:
597:
593:
590:presentation
589:
585:
581:
577:
573:
569:
567:
563:
555:
552:
548:
545:
541:
540:
539:
536:
534:
530:
526:
522:
518:
514:
508:
506:
502:
498:
493:
485:
480:
475:
467:
465:
463:
459:
455:
451:
446:
444:
440:
436:
432:
430:
426:
422:
418:
414:
410:
406:
402:
398:
397:Edgar F. Codd
394:
389:
387:
383:
382:network model
379:
375:
371:
366:
364:
360:
356:
355:magnetic tape
352:
348:
347:storage media
344:
340:
336:
332:
324:
322:
320:
316:
312:
308:
304:
300:
296:
291:
289:
284:
282:
278:
274:
271:
267:
263:
259:
255:
251:
246:
244:
236:
233:
230:
227:
224:
221:
218:
215:
214:
213:
210:
208:
204:
200:
195:
192:
189:
185:
177:
175:
173:
169:
165:
161:
157:
153:
149:
145:
141:
137:
135:
131:
127:
123:
119:
115:
111:
110:data modeling
107:
103:
102:cloud storage
99:
95:
90:
88:
84:
80:
76:
72:
68:
64:
61:or a type of
60:
56:
52:
44:
39:
33:
19:
6929:Microformats
6868:Common Logic
6573:Applications
6502:
6489:Semantic Web
6418:Dan Linstedt
6004:
5614:
5484:
5437:
5427:
5417:Log shipping
5361:Online music
5346:Biodiversity
5313:Preservation
5071:Requirements
5056:
4947:Cyberwarfare
4606:Cryptography
4522:
3972:
3965:
3958:
3944:
3926:
3916:
3900:
3886:
3879:
3836:
3816:
3795:
3781:
3758:
3741:
3736:
3710:
3706:
3678:
3654:
3629:
3625:
3603:. Retrieved
3589:
3572:
3555:
3539:. Retrieved
3530:
3507:
3488:
3484:
3436:
3430:
3418:. Retrieved
3408:
3396:
3369:
3363:
3328:
3324:
3314:
3305:
3295:
3283:
3272:. Retrieved
3262:
3255:Chapple 2005
3250:
3238:
3226:
3214:
3202:
3190:
3178:
3166:. Retrieved
3157:
3148:
3140:
3124:
3108:
3096:
3084:. Retrieved
3064:
3054:
3047:
3040:Childs 1968b
3035:
3028:Childs 1968a
3023:
3011:
2999:
2987:
2975:. Retrieved
2965:
2950:. Retrieved
2945:
2936:
2927:
2918:
2911:Bachman 1973
2906:
2894:
2882:
2870:
2857:
2848:
2835:
2826:
2813:
2804:
2799:, p. 1.
2792:
2773:
2634:
2628:
2622:
2620:, and more.
2594:IBM Research
2587:
2578:
2572:
2570:
2565:
2558:
2544:
2540:
2533:
2529:
2522:
2516:
2479:XML database
2473:
2453:
2435:
2432:
2413:Object model
2368:
2361:
2335:
2322:
2320:
2312:
2307:
2303:
2299:
2295:
2284:
2272:
2257:
2231:
2219:
2201:
2188:
2179:
2161:
2157:
2148:
2128:
2095:The acronym
2094:
2072:
2053:
2039:
2031:
2027:
2020:
2001:
1986:
1959:
1950:
1933:
1929:
1927:
1900:
1893:
1888:file systems
1880:preservation
1874:
1870:
1858:
1854:
1852:
1820:
1753:
1723:sublanguages
1720:
1699:preprocessor
1676:
1664:
1632:
1605:
1602:
1594:
1586:
1552:
1533:
1506:
1434:
1428:
1420:
1385:transactions
1353:
1349:
1301:triplestores
1272:
1252:maintenance.
1152:
1124:
1117:
1102:
1093:
1078:Please help
1066:
1035:
1016:
1008:denormalized
1002:
991:
944:
920:
900:
889:
878:
868:
859:
855:
844:
842:
831:and Oracle (
817:
801:
755:
750:
724:
700:
696:
691:
688:
684:
676:
660:
655:
651:
632:
627:
613:
591:
588:Turing Award
570:
559:
550:
537:
532:
509:
491:
489:
447:
433:
401:applications
390:
367:
359:navigational
328:
307:mobile phone
292:
285:
270:multitasking
247:
240:
234:
228:
222:
216:
211:
202:
196:
193:
186:that allows
181:
138:
91:
86:
83:applications
70:
66:
54:
48:
6965:Dublin Core
6691:Library 2.0
6559:Linked data
6355:Spreadsheet
6288:Data mining
6030:Star schema
5934:WikiProject
5825:Replication
5713:Transaction
5655:Foreign key
5635:CAP theorem
5582:Multi-model
5434:WikiProject
5263:Programming
5254:Cardinality
5249:Refactoring
5106:Application
4957:Video games
4937:Digital art
4694:Concurrency
4563:Data mining
4475:Probability
4208:Interpreter
3796:Data Models
3673:Date, C. J.
3288:Wagner 2010
3168:10 December
2641:conferences
2494:Event store
2464:Array model
2428:Star schema
2105:consistency
1941:Replication
1857:(physical)
1655:Application
1628:web browser
1624:web servers
1453:fuzzy logic
1331:hyperlinked
1284:, to allow
1194:web browser
1167:main memory
1141:that store
1137:, and many
1027:consistency
1019:CAP theorem
927:Lotus 1-2-3
762:D.L. Childs
718:, known as
716:data access
643:primary key
635:linked list
598:. IDMS and
370:data models
319:scalability
207:spreadsheet
201:, the term
132:access and
94:file system
7051:Categories
6975:Schema.org
6711:References
6661:Geotagging
6656:Folksonomy
6549:Dataspaces
6542:Sub-topics
6518:Ontologies
6496:Background
6394:Bill Inmon
6198:Degenerate
6167:Fact table
5799:Query plan
5752:Components
5670:Unique key
5587:comparison
5521:comparison
5511:Relational
5504:comparison
5407:Publishing
5341:Biological
5284:Management
5116:datasource
5111:Connection
5015:Glossaries
4887:E-commerce
4480:Statistics
4423:Algorithms
4381:Stochastic
4213:Middleware
4069:Peripheral
3782:Dr. Dobb's
3541:28 January
3388:1029759767
3274:2007-06-10
3016:North 2010
2946:OED Online
2785:References
2710:Data store
2602:prototypes
2304:data model
2296:data model
2221:query plan
2123:See also:
2113:durability
2034:privileges
2004:March 2013
1945:See also:
1687:datasource
1679:programmer
1540:relational
1517:PostgreSQL
1327:hypermedia
1312:array DBMS
1278:middleware
1256:databases.
1188:relies on
1096:March 2013
955:attributes
885:data store
881:PostgreSQL
860:Database 2
811:, and the
751:relational
692:normalized
584:System/360
363:relational
331:processors
295:relational
277:networking
130:concurrent
63:data store
7062:Databases
7006:hCalendar
6924:Microdata
6821:N-Triples
6814:Notation3
6740:Standards
6716:Topic map
6554:Hyperdata
6523:Semantics
6508:Hypertext
6503:Databases
6312:Languages
6298:OLAP cube
6283:Dashboard
6234:Transform
6186:Dimension
6141:Data mart
6076:Data mesh
6045:Aggregate
6010:Dimension
5808:Functions
5743:Partition
5570:In-memory
5528:Key–value
5402:Load file
5318:Integrity
5308:Migration
5235:notation)
5206:Forensics
5153:Languages
4836:Rendering
4831:Animation
4462:computing
4413:Semantics
4104:Processor
3727:1477-8424
3646:207549016
3570:(1968b).
3553:(1968a).
3531:Databases
3460:Date 2003
3420:April 15,
3355:253467923
3347:2631-7680
3086:23 August
2992:Codd 1970
2705:Data bank
2616:methods,
2449:Flat file
2439:include:
2119:Migration
2109:isolation
2101:atomicity
1996:talk page
1817:with SQL.
1813:combines
1797:MarkLogic
1689:) via an
1608:terminals
1366:knowledge
1362:retrieval
1323:hypertext
1226:combines
1213:ACNielsen
1198:Open APIs
1129:systems,
1067:does not
1048:Use cases
892:Mimer SQL
760:based on
735:Honeywell
652:relations
623:hard disk
372:were the
229:Retrieval
79:end users
51:computing
7016:hProduct
6706:Metadata
6513:Internet
6427:Products
6271:Concepts
6136:Metadata
6125:Elements
6071:Data hub
6059:Variants
6005:Database
5998:Concepts
5914:Category
5830:Sharding
5686:Relation
5660:Superkey
5615:Database
5608:Concepts
5444:Category
5375:See also
5336:Academic
5328:Lists of
5233:Enhanced
5188:Security
5057:Database
4995:Category
4823:Graphics
4598:Security
4260:Compiler
4159:Networks
4056:Hardware
3861:Ling Liu
3786:Archived
3675:(2003).
3617:(1970).
3605:17 March
3535:Archived
3479:(1973).
3441:Archived
3133:Archived
3077:Archived
2952:July 12,
2862:Archived
2840:Archived
2818:Archived
2666:See also
2590:academia
2584:Research
2279:workflow
1968:Security
1863:metadata
1855:internal
1641:such as
1415:hardware
1143:websites
846:System R
809:Teradata
712:System R
492:database
386:pointers
376:and the
349:such as
203:database
118:security
75:software
55:database
7026:hReview
7021:hRecipe
6793:JSON-LD
6786:RDF/XML
6779:triples
6721:Web 2.0
6377:Related
6229:Extract
6212:Filling
6177:Measure
5924:Outline
5723:Trigger
5679:Objects
5301:caching
5091:Machine
5005:Outline
3469:Sources
2977:Feb 20,
2730:Datalog
2662:ICDE).
2643:(e.g.,
2633:-TODS,
2549:indexes
1839:Storage
1811:SQL/XML
1711:ADO.NET
1513:MariaDB
1451:employ
1127:library
1088:removed
1073:sources
951:objects
864:IBM Db2
833:Exadata
829:Netezza
743:Multics
669:In the
582:on the
562:B-trees
544:hashing
525:CODASYL
523:within
484:CODASYL
413:IBM Db2
380:model (
378:CODASYL
325:History
309:), the
250:servers
156:columns
122:privacy
73:), the
6939:SAWSDL
6842:SPARQL
6800:Turtle
6387:People
5738:Cursor
5696:column
5565:NewSQL
5356:Online
5296:Tuning
5244:Schema
5221:Design
5101:Server
5096:Engine
5081:Models
5076:Theory
3951:
3933:
3871:
3843:
3824:
3803:
3765:
3725:
3687:
3661:
3644:
3596:
3514:
3386:
3376:
3353:
3345:
3116:
2650:, ACM
2648:SIGMOD
2606:models
2598:theory
2344:Models
2287:schema
2235:DevOps
2176:Backup
2164:tuning
2111:, and
1815:XQuery
1793:XQuery
1787:EJB QL
1527:, and
1316:arrays
1217:mining
1037:NewSQL
988:NewSQL
874:Oracle
856:SQL/DS
780:, and
776:, the
768:, the
737:wrote
707:INGRES
639:tables
499:. The
462:NewSQL
423:, and
417:Oracle
405:entity
361:, SQL/
341:, and
315:XQuery
288:market
273:kernel
223:Update
160:tables
104:. The
7011:hCard
7001:hAtom
6919:GRDDL
6898:SHACL
6671:iXBRL
6630:Solid
6338:Tools
6111:ROLAP
6106:MOLAP
6101:HOLAP
5728:Index
5691:table
5594:Cloud
5560:NoSQL
5555:Graph
5492:Types
5231:(and
5201:Audit
5171:Query
5143:Tools
5138:Types
4408:Logic
4242:tools
3703:(PDF)
3642:S2CID
3622:(PDF)
3577:(PDF)
3560:(PDF)
3351:S2CID
3080:(PDF)
3073:(PDF)
2765:Notes
2566:views
2086:crash
1960:With
1859:level
1805:Saxon
1801:eXist
1783:JDOQL
1681:will
1648:email
1509:MySQL
1321:In a
1004:NoSQL
984:NoSQL
931:dBASE
656:views
604:TOTAL
529:COBOL
450:NoSQL
421:MySQL
305:to a
188:users
168:NoSQL
6985:SKOS
6980:SIOC
6970:FOAF
6960:DOAP
6934:RDFa
6914:eRDF
6893:ALPS
6878:RDFS
6837:RRID
6828:TriX
6807:TriG
6754:HTTP
6239:Load
6160:Fact
6025:OLAP
6020:Fact
5779:ODBC
5769:JDBC
5708:View
5645:Null
5640:CRUD
5620:ACID
5575:list
5538:list
5516:list
5133:Lock
5064:Main
4240:and
4113:Form
4109:Size
3949:ISBN
3931:ISBN
3895:and
3869:ISBN
3841:ISBN
3822:ISBN
3801:ISBN
3763:ISBN
3723:ISSN
3685:ISBN
3659:ISBN
3607:2013
3594:ISBN
3543:2009
3512:ISBN
3422:2017
3384:OCLC
3374:ISBN
3343:ISSN
3170:2010
3114:ISBN
3088:2017
2979:2014
2954:2013
2740:DBOS
2660:IEEE
2656:VLDB
2652:PODS
2618:RAID
2543:(or
2539:The
2532:(or
2528:The
2521:The
2364:data
2298:and
2097:ACID
2090:lock
2080:and
1910:and
1873:and
1847:and
1799:and
1785:and
1709:and
1707:JDBC
1703:ODBC
1683:code
1622:and
1555:Codd
1303:and
1209:UPCs
1196:and
1071:any
1069:cite
1042:ACID
986:and
965:and
824:CAFS
741:for
739:MRDS
727:PRTV
720:QUEL
551:sets
456:and
429:DBMS
391:The
258:RAID
154:and
152:rows
120:and
71:DBMS
59:data
53:, a
6873:OWL
6847:XML
6773:RDF
6765:URI
6759:IRI
5774:XQJ
5701:row
5121:DSN
3746:doi
3715:doi
3634:doi
3493:doi
3333:doi
2645:ACM
2051:).
1775:OQL
1643:SQL
1493:An
1477:SQL
1364:of
1325:or
1310:An
1247:An
1172:An
1161:An
1122:).
1082:by
997:XML
866:).
835:).
822:'s
820:ICL
572:IBM
566:API
299:XML
297:or
164:SQL
100:or
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43:SQL
41:An
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3899:,
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