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ArangoDB

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as a default storage format, but internally it uses ArangoDB VelocyPack – a fast and compact binary format for serialization and storage. ArangoDB can natively store a nested JSON object as a data entry inside a collection. Therefore, there is no need to disassemble the resulting JSON objects. Thus,
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ArangoDB GmbH was founded in 2014 by Claudius Weinberger and Frank Celler. They originally called the database system “A Versatile Object Container", or AVOC for short, leading them to call the database AvocadoDB. Later, they changed the name to ArangoDB. The word "arango" refers to a little-known
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In January 2017 ArangoDB raised a seed round investment of 4.2 million Euros led by Target Partners. In March 2019 ArangoDB raised 10 million dollars in series A funding led by Bow Capital. In October 2021 ArangoDB raised 27.8 million dollars in series B funding led by
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Commercial self-managed: ArangoDB Enterprise is a paid subscription that includes graph-aware sharding (called “SmartGraphs”) and collection replication (called “Satellite Collections”) to reduce query times, and increased
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Collections replicated on all cluster nodes can be combined with graphs sharded by document attributes to enable more local execution of graph queries ("Hybrid SmartGraphs", "Hybrid Disjoint SmartGraphs").
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Kubernetes: ArangoDB runs on Kubernetes, including cloud-based Kubernetes services Amazon Elastic Kubernetes Service (EKS), Google Kubernetes Engine (GKE), and Microsoft Azure Kubernetes Service (AKS).
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is a system for large scale graph processing. Pregel is implemented in ArangoDB and can be used with predefined algorithms, e.g. PageRank, Single-Source Shortest Path and Connected components.
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Option to store all collections of a database on a single cluster node, to combine the performance of a single server and ACID semantics with a fault-tolerant cluster setup ("OneShard").
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Community Edition: ArangoDB Community Edition is a graph database with native multi-model database capabilities written mainly in C++ and was available under an open-source license (
1388:"ArangoDB Announces $ 27.8 Million Series B Investment to Accelerate Development of Next-Generation Graph ML, Providing Advanced Analytics and AI Capabilities at Enterprise Scale" 1904: 1070:). ArangoDB Oasis provides the functionality of an ArangoDB cluster deployment while minimizing the amount of administrative effort required. ArangoDB Oasis run on multiple 395:
Graph traversal algorithms to enumerate all paths between two vertices ("k Paths") and to emit paths in order of increasing edge weights ("Weighted Traversals").
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Late document materialization to only fetch the relevant documents from SORT/LIMIT queries and early pruning of non-matching documents in full collection scans.
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Search: ArangoDB's search engine combines boolean retrieval capabilities with generalized ranking components allowing for data retrieval based on a precise
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Flexible data field pre-processing with custom queries ("AQL Analyzer") and the ability to chain built-in and custom analyzers ("Pipeline Analyzer").
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AQL (ArangoDB Query Language). AQL is mainly a declarative language and allows the combination of different data access patterns in a single query.
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Predictable performance: ArangoDB is written mainly in C++ and manages its own memory to avoid unpredictable performance arising from
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Transactions: ArangoDB supports user-definable transactions. Transactions in ArangoDB are atomic, consistent, isolated, and durable (
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Insert operations can be turned into a replace automatically, in case that the target document already exists ("Repsert").
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Support for computed values (persistent document attributes that are generated when a document is created or updated).
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Multiple query languages: The database has its own query language, AQL (ArangoDB Query Language), and also provides
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Collections replicated on all cluster nodes to execute joins with sharded data locally ("SatelliteCollections").
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Value-based sharding of large graph datasets for better data locality when traversing graphs ("SmartGraphs").
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Cloud: ArangoDB is offered as a cloud service called Oasis, providing ArangoDB databases as a Service (
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Multi-document transactions with individual begin and commit / abort commands ("Stream Transactions").
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Support for sliding window queries to aggregate adjacent documents, value ranges and time intervals.
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A graph traversal algorithm to query for all paths with the shortest value, between two documents.
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Data masking capabilities for attributes containing sensitive data / PII when creating backups.
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Graphs replicated on all cluster nodes to execute graph traversals locally ("SatelliteGraphs").
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Support for vertex-centric indexes for more efficient graph traversals with filter conditions.
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Key rotation for superuser JWT tokens, TLS certificates, and on-disk encryption keys.
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Co-located joins in a cluster using identically sharded collections ("SmartJoins").
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Distributed iterative graph processing with Pregel in single server and cluster.
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Integrated full-text search and information retrieval engine ("ArangoSearch").
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Graph traversal algorithm to get multiple shortest paths ("k Shortest Paths").
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Custom text pre-processors for full-text search ("Configurable Analyzers").
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the stored data would simply inherit the tree structure of the JSON data.
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Low-latency request handling using a boost-ASIO server infrastructure.
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Stop condition support for graph traversals ("Pruning in Traversals").
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Datacenter to Datacenter Replication for disaster recovery ("DC2DC").
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Reliability: ArangoDB provides datacenter-to-datacenter replication.
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Cluster support with synchronous replication and automatic failover.
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Improved user experience for database administration and management.
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microservices directly on top of the DBMS using the Foxx framework.
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to write flexible native web services directly on top of the DBMS.
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operations for both documents (nodes) and edges, but it is not a
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Language-agnostic tokenization of text ("Segmentation Analyzer").
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Persistent indexes that are stored on disk for faster restarts.
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Time-based removal of expired documents ("Time-to-live Index").
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Native implementations in C++ of all built-in query functions.
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Deployment mode for single servers with automatic failover.
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Geo-spatial queries can be combined with full-text search.
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Microservices: ArangoDB provides integration with native
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Round-robin load-balancer support for cloud environments.
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Inlining of certain subqueries to improve execution time.
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Parallel execution of queries on several cluster nodes.
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Wildcard and fuzzy search support for full-text search.
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Query profiling to show detailed runtime information.
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Data science and analytics operational enhancements.
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system since it supports three data models (graphs,
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Support for composable, distance-based geo-queries.
223:database system but AQL is similar in many ways to 177: 164: 136: 122: 91: 65: 43: 33: 327:Native ARM support, including native support for 295:Faster query performance across search and graph. 1659:"Transactions | Manual | ArangoDB Documentation" 1434:AvocadoDB Query Language Jan Steemann in english 1294:AvocadoDB Query Language Jan Steemann in english 858:// Count the number of documents in a collection 551:Improved geo-spatial index with GeoJSON support. 200:system developed by ArangoDB Inc. ArangoDB is a 1729:"ArangoDB SmartGraphs | ArangoDB Documentation" 686:Improved query editor and query explain output. 1105:"Advantages of native multi-model in ArangoDB" 677:New viewer for large graphs, supporting WebGL. 1548:"Foxx Microservices | ArangoDB Documentation" 8: 1500:"DC2DC Replication | ArangoDB Documentation" 19: 569:Multi-threaded dump and restore operations. 518:Consistent snapshot backup in cluster mode. 1905:Software using the Business Source License 111: 18: 894:// Add a new document into our collection 1618:"Stanford University Pregel White paper" 837:// Return every document in a collection 563:Cluster-distributed aggregation queries. 407:Hardware-accelerated on-disk encryption. 255: 1096: 1074:, include AWS, Azure, and Google Cloud. 212:) with one database core and a unified 436:Document validation using JSON Schema. 809:AQL (ArangoDB Query Language) is the 718:Binary storage format ("VelocyPack"). 7: 680:Binary wire format ("VelocyStream"). 639:Export utility for multiple formats. 1895:Database-related software for Linux 1362:Weinberger, Claudius (2019-03-14). 1085:Comparison of multi-model databases 805:), but only if data is not sharded. 1890:Distributed computing architecture 14: 72:3.11.5 / November 9, 2023 1860:Free database management systems 1314:""AvocadoDB" becomes "ArangoDB"" 173:1.1 and Arango Community License 25: 337:Parallelism for sharded graphs. 240:avocado variety grown in Cuba. 1777:"ArangoDB Enterprise Features" 1178:"ArangoDB's design objectives" 1: 633:Fault-tolerant microservices. 1176:Celler, Frank (2012-03-07). 1875:Document-oriented databases 1249:Ortell, Bill (2021-03-08), 760:Scaling: ArangoDB provides 642:Encryption of on-disk data. 49:; 13 years ago 1921: 151:Document-oriented database 87: 61: 24: 834: 821:(DDL). AQL does support 819:data definition language 1072:cloud service providers 171:Business Source License 159:Full-text Search Engine 74:; 10 months ago 1711:, ArangoDB, 2023-10-13 1576:, ArangoDB, 2022-08-05 1458:, ArangoDB, 2022-08-05 1343:www.avocadosource.com 1230:www.avocadosource.com 267:Latest Minor Version 231:as a storage engine. 745:JSON: ArangoDB uses 645:LDAP authentication. 202:multi-model database 143:Multi-model database 16:Multi-model database 1900:Key-value databases 1413:AvocadoDB explained 1273:AvocadoDB explained 764:through clustering. 257: 21: 1885:Structured storage 1339:"Variety Database" 1226:"Variety Database" 794:Pregel algorithm: 789:vector space model 755:garbage collection 598:Encrypted backups. 256: 155:Key/Value database 737: 736: 191: 190: 1912: 1839: 1838: 1836: 1835: 1825:"ArangoDB Oasis" 1821: 1815: 1814: 1812: 1811: 1805:www.arangodb.com 1797: 1791: 1790: 1788: 1787: 1773: 1767: 1766: 1764: 1763: 1757:www.arangodb.com 1749: 1743: 1742: 1740: 1739: 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