96:
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682:. The implementation uses Numpy arrays (themselves Python wrappers for C arrays), as a result there is limited overhead - providing a functional Python integration with speed matching native SQL functions. The Embedded Python functions also support mapped operations, allowing user to execute Python functions in parallel within SQL queries. The practical side of the feature gives users access to Python/NumPy/
27:
392:
back-end layer provides a number of cost-based optimizers for the MAL. The bottom layer is the database kernel, which provides access to the data stored in Binary
Association Tables (BATs). Each BAT is a table consisting of an Object-identifier and value columns, representing a single column in the database.
561:
fashion, only when needed. The system can also process the data upon ingestion, if the data format requires it. As a result, even very large file repositories can be efficiently analyzed, as only the required data is processed in the database. The data can be accessed through either the MonetDB SQL
702:. It is distributed as an R package, removing the need to manage a database server, required for the previous R integrations. The DBMS runs within the R process itself, eliminating socket communication and serialisation overhead - greatly improving efficiency. The idea behind it is to deliver an
407:
Query recycling is an architecture for reusing the byproducts of the operator-at-a-time paradigm in a column store DBMS. Recycling makes use of the generic idea of storing and reusing the results of expensive computations. Unlike low-level instruction caches, query recycling uses an optimizer to
657:
connector allowed the using MonetDB data sources and process them in an R session. The newer R integration feature of MonetDB does not require data to be transferred between the RDBMS and the R session, reducing overhead and improving performance. The feature is intended to give users access to
391:
interfaces under development. Queries are parsed into domain-specific representations, like relational algebra for SQL, and optimized. The generated logical execution plans are then translated into MonetDB Assembly
Language (MAL) instructions, which are passed to the next layer. The middle or
428:
MonetDB was one of the first databases to introduce
Database Cracking. Database Cracking is an incremental partial indexing and/or sorting of the data. It directly exploits the columnar nature of MonetDB. Cracking is a technique that shifts the cost of index maintenance from updates to query
317:
In 2011 a major effort to renovate the MonetDB codebase was started. As part of it, the code for the MonetDB 4 kernel and its XQuery components were frozen. In MonetDB 5, parts of the SQL layer were pushed into the kernel. The resulting changes created a difference in internal
441:
A number of extensions exist for MonetDB that extend the functionality of the database engine. Due to the three-layer architecture, top-level query interfaces can benefit from optimizations done in the backend and kernel layers.
429:
processing. The query pipeline optimizers are used to massage the query plans to crack and to propagate this information. The technique allows for improved access times and self-organized behavior. Database
Cracking received the
500:
project, together with the Data Vault technology, providing transparent access to large scientific data repositories. Data Vaults map the data from the distributed repositories to SciQL arrays, allowing for improved handling of
269:) was released on September 30, 2004. When MonetDB version 4 was released into the open-source domain, many extensions to the code base were added by the MonetDB/CWI team, including a new SQL front end, supporting the
334:
and persistent indices. In this release the deprecated streaming data module DataCell was also removed from the main codebase in an effort to streamline the code. In addition, the license has been changed into the
1883:
Ivanova, Milena; Kargin, Yagiz; Kersten, Martin; Manegold, Stefan; Zhang, Ying; Datcu, Mihai; Molina, Daniela
Espinoza (2013). "Data Vaults: A Database Welcome to Scientific File Repositories".
1311:
Ivanova, Milena; Kargin, Yagiz; Kersten, Martin; Manegold, Stefan; Zhang, Ying; Datcu, Mihai; Molina, Daniela
Espinoza (2013). "Data Vaults: A Database Welcome to Scientific File Repositories".
322:, as it transitioned from MonetDB Instruction Language (MIL) to MonetDB Assembly Language (MAL). Older, no-longer maintained top-level query interfaces were also removed. First was
653:
to be executed in the SQL layer of the system. This is done using the native R support for running embedded in another application, inside the RDBMS in this case. Previously the
1773:
Kersten, Martin L; Idreos, Stratos; Manegold, Stefan; Liarou, Erietta (2011). "The researcher's guide to the data deluge: Querying a scientific database in just a few seconds".
744:
408:
pre-select instructions to cache. The technique is designed to improve query response times and throughput, while working in a self-organizing fashion. The authors from the
2470:
1618:
Sidirourgos, Lefteris; Goncalves, Romulo; Kersten, Martin; Nes, Niels; Manegold, Stefan (2008). "Column-store support for RDF data management: not all swans are white".
2475:
1259:
Zhang, Y.; Scheers, L. H. A.; Kersten, M. L.; Ivanova, M.; Nes, N. J. (2011). "Astronomical Data
Processing Using SciQL, an SQL Based Query Language for Array Data".
942:
2515:
739:
383:
MonetDB architecture is represented in three layers, each with its own set of optimizers. The front end is the top layer, providing query interface for
1639:
Ivanova, Milena G.; Kersten, Martin L.; Nes, Niels J.; Goncalves, Romulo A.P. (2009). "An
Architecture for Recycling Intermediates in a Column-store".
2500:
1964:
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standard. The Data Vault technology allows for transparent integration with distributed/remote file repositories. It is designed for scientific data
1829:
Ivanova, Milena; Kersten, Martin; Manegold, Stefan (2012). "Data vaults: a symbiosis between database technology and scientific file repositories".
1279:
Ivanova, Milena; Kersten, Martin; Manegold, Stefan (2012). "Data vaults: a symbiosis between database technology and scientific file repositories".
478:
SciQL an SQL-based query language for science applications with arrays as first class citizens. SciQL allows MonetDB to effectively function as an
234:
called Data
Distilleries, which used early MonetDB implementations in its analytical suite. Data Distilleries eventually became a subsidiary of
2505:
1800:
Liarou, Erietta; Idreos, Stratos; Manegold, Stefan; Kersten, Martin (2012). "MonetDB/DataCell: online analytics in a streaming column-store".
399:
of memory mapped files, and thus departing from traditional DBMS designs involving complex management of large data stores in limited memory.
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A number of former extensions have been deprecated and removed from the stable code base over time. Some notable examples include an
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functions of the R statistical software for in-line analysis of data stored in the RDBMS. It complements the existing support for
2485:
1428:
1171:
330:
interface support was removed with the
October 2014 release. With the July 2015 release, MonetDB gained support for read-only
2342:
623:
212:
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1957:
858:
675:
208:
2321:
2022:
299:. MonetDB includes automatic and self-tuning indexes, run-time query optimization, and a modular software architecture.
200:
69:
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50:
1001:
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2007:
749:
467:
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2300:
2200:
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Kersten, M; Zhang, Ying; Ivanova, Milena; Nes, Niels (2011). "SciQL, a query language for science applications".
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829:
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1950:
949:. In Proceedings of the ACM SIGMOD International Conference on Management of Data, Chicago, IL, USA, June 2006.
659:
650:
109:
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MonetDB/SQL is a top-level extension, which provides complete support for transactions in compliance with the
795:
199:
with hundreds of columns and millions of rows. MonetDB has been applied in high-performance applications for
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502:
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MonetDB internal data representation also relies on the memory addressing ranges of contemporary CPUs using
289:
254:
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formats. The data is stored in the file repository in the original format, and loaded in the database in a
195:. It is designed to provide high performance on complex queries against large databases, such as combining
2316:
2113:
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1016:
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Proceedings of the International Workshop on Performance and Evaluation of Data Management Systems (ExpDB)
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463:
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266:
149:
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2017:
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2012:
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Idreos, S.; Groffen, F. E.; Nes, N. J.; Manegold, S.; Mullender, K. S.; Kersten, M. L. (March 2012).
754:
262:
181:
178:
133:
1874:
Sidirourgos, Lefteris & Kersten, Martin (2013). "Column imprints: a secondary index structure".
1021:
698:) and R UDFs in MonetDB (MonetDB/R), the authors created an embedded version of MonetDB in R called
227:
Data mining projects in the 1990s required improved analytical database support. This resulted in a
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2169:
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2037:
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571:
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128:
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Proceedings of the 25th International Conference on Scientific and Statistical Database Management
1313:
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
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26:
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Kargin, Yagiz; Ivanova, Milena; Zhang, Ying; Manegold, Stefan; Kersten, Martin (August 2013).
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1400:
1368:
1344:
Kargin, Yagiz; Ivanova, Milena; Zhang, Ying; Manegold, Stefan; Kersten, Martin (August 2013).
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972:
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Similarly to the embedded R UDFs in MonetDB, the database now has support for UDFs written in
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413:
311:
250:
2326:
2032:
1888:
1854:
1809:
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1598:
1550:
1360:
1316:
1145:
1026:
964:
914:
631:
522:
284:-tuned query execution architecture that often gave MonetDB a speed advantage over the same
196:
144:
116:
1795:. CIDR 2011: 5th Biennial Conference on Innovative Data Systems Research. Creative Commons.
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2190:
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for Earth observation data. Data Vaults for FITS files have also been used for processing
558:
493:
95:
1080:
366:
Please help update this section to reflect recent events or newly available information.
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By 2008, a follow-on project called X100 (MonetDB/X100) started, which evolved into the
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530:
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Data Vault is a database-attached external file repository for MonetDB, similar to the
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331:
121:
39:
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research, the module has a SAM/BAM data loader and a set of SQL UDFs for working with
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2403:
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1432:
409:
396:
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706:-like package for R, with the performance of an in-memory optimized columnar store.
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libraries, which can provide a large selection of statistical/analytical functions.
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Ivanova, Milena G; Kersten, Martin L; Nes, Niels J; Goncalves, Romulo AP (2010).
1641:
Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data
1549:. Lecture Notes in Computer Science. Vol. 1997. Springer. pp. 137–150.
1132:
Ivanova, Milena G; Kersten, Martin L; Nes, Niels J; Goncalves, Romulo AP (2010).
961:
Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
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326:, which relied on MonetDB 4 and was never ported to version 5. The experimental
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257:. It was initially called simply Monet, after the French impressionist painter
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Schmidt, Albrecht; Kersten, Martin; Windhouwer, Menzo; Waas, Florian (2001).
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P. A. Boncz, T. Grust, M. van Keulen, S. Manegold, J. Rittinger, J. Teubner.
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1103:"MonetDB: Two Decades of Research in Column-oriented Database Architectures"
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296:
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295:. It was one of the first database systems to tune query optimization for
245:
MonetDB in its current form was first created in 2002 by doctoral student
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2002:
607:
451:
270:
1928:
Database Architectures group at CWI - the original developers of MonetDB
1668:"Optimizing Database Architecture for the New Bottleneck: Memory Access"
959:
Marcin Zukowski; Peter Boncz (May 20, 2012). "From x100 to vectorwise".
416:, Niels Nes and Romulo Goncalves, won the "Best Paper Runner Up" at the
534:
518:
1937:
1876:
Proceedings of the 2013 international conference on Management of data
1793:
SciBORQ: Scientific data management with Bounds On Runtime and Quality
940:
MonetDB/XQuery: A Fast XQuery Processor Powered by a Relational Engine
812:
622:-based extension for working with linked data, which adds support for
1530:
Database architecture optimized for the new bottleneck: Memory access
860:
Monet: A Next-Generation DBMS Kernel For Query-Intensive Applications
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Manegold, Stefan; Boncz, Peter A.; Kersten, Martin L. (Dec 2000).
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843:
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Open source column-oriented relational database management system
1534:
Proceedings of International Conference on Very Large Data Bases
719:
542:
462:
MonetDB/GIS is an extension to MonetDB/SQL with support for the
327:
235:
2373:
2257:
1984:
1946:
1709:"An architecture for recycling intermediates in a column-store"
1134:"An architecture for recycling intermediates in a column-store"
562:
or SciQL interfaces. The Data Vault technology was used in the
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1708:
1667:
1586:
1542:
1133:
1000:
Inkster, D.; Zukowski, M.; Boncz, P. A. (September 20, 2011).
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346:
281:
239:
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Sidirourgos, Lefteris; Kersten, Martin; Boncz, Peter (2011).
1784:
Proceedings of the EDBT/ICDT 2011 Workshop on Array Databases
1572:
Idreos, Stratos; Kersten, Martin L; Manegold, Stefan (2007).
1543:"Efficient Relational Storage and Retrieval of XML Documents"
1216:
Idreos, Stratos; Kersten, Martin L; Manegold, Stefan (2007).
1585:
Boncz, Peter A; Kersten, Martin L; Manegold, Stefan (2008).
1504:"Announcement: New Oct2014 Feature release of MonetDB suite"
1283:. SSDBM 20212. Springer Berlin Heidelberg. pp. 485–494.
1172:"CWI database team wins Best Paper Runner Up at SIGMOD 2009"
813:"MonetDB - LOD2 - Creating Knowledge out of Interlined Data"
486:
280:: a storage model based on vertical fragmentation, a modern
1923:
MonetDB Solutions - MonetDB's professional services company
1833:. SSDBM 2012. Springer Berlin Heidelberg. pp. 485–494.
1917:
1840:"Lazy ETL in Action: ETL Technology Dates Scientific Data"
1346:"Lazy ETL in Action: ETL Technology Dates Scientific Data"
866:(Ph.D. Thesis). Universiteit van Amsterdam. Archived from
412:
Database Architectures group, composed of Milena Ivanova,
161:
1528:
Boncz, Peter; Manegold, Stefan; Kersten, Martin (1999).
505:
data in MonetDB. SciQL will be further extended for the
1387:"Astronomical data analysis with MonetDB Data Vaults"
745:
Comparison of relational database management systems
276:
MonetDB introduced innovations in all layers of the
2424:
2384:
2335:
2309:
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2209:
2183:
2157:
2122:
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1995:
420:2009 conference for their work on Query Recycling.
156:
143:
127:
115:
105:
68:
49:
33:
253:as part of the 1990s' MAGNUM research project at
1740:Goncalves, Romulo & Kersten, Martin (2011).
1261:Astronomical Data Analysis Software and Systems
1831:Scientific and Statistical Database Management
1678:(3). Springer-Verlag New York, Inc.: 231–246.
1281:Scientific and Statistical Database Management
900:"An Empirical Evaluation of XQuery Processors"
740:List of relational database management systems
694:Following the release of remote driver for R (
2437:Data warehousing products and their producers
1958:
1096:
1094:
1092:
1090:
8:
1742:"The data cyclotron query processing scheme"
19:
2381:
2370:
2265:
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1992:
1981:
1965:
1951:
1943:
718:extension removed in MonetDB version 5; a
94:
18:
2471:Client-server database management systems
1933:List of scientific projects using MonetDB
1020:
882:
880:
824:
822:
2476:Column-oriented DBMS software for Linux
1306:
1304:
1274:
1272:
1270:
1002:"Integration of VectorWise with Ingres"
770:
570:project, which was aimed at building a
306:technology. VectorWise was acquired by
238:in 2003, which in turn was acquired by
2516:Relational database management systems
626:and allowing MonetDB to function as a
1643:. SIGMOD '09. ACM. pp. 309–320.
1587:"Breaking the memory wall in MonetDB"
807:
805:
790:
788:
433:2011 J.Gray best dissertation award.
185:relational database management system
7:
1746:ACM Transactions on Database Systems
1713:ACM Transactions on Database Systems
1138:ACM Transactions on Database Systems
844:"A short history about us - MonetDB"
662:UDFs and is intended to be used for
187:(RDBMS) originally developed at the
594:module for efficient processing of
337:Mozilla Public License, version 2.0
265:license (a modified version of the
2322:MultiDimensional eXpressions (MDX)
1938:MonetDB.R - MonetDB to R Connector
1455:"Embedded Python/NumPy in MonetDB"
1431:. 13 November 2014. Archived from
606:data. The module uses the popular
580:The INT Photometric H-Alpha Survey
314:and sold as a commercial product.
189:Centrum Wiskunde & Informatica
14:
1847:Proceedings of the VLDB Endowment
1802:Proceedings of the VLDB Endowment
1620:Proceedings of the VLDB Endowment
1353:Proceedings of the VLDB Endowment
2501:Free database management systems
1547:The World Wide Web and Databases
351:
25:
1067:"MonetDB Oct2014 Release Notes"
533:data. There is support for the
2343:Business intelligence software
2222:Extract, load, transform (ELT)
2217:Extract, transform, load (ETL)
1110:IEEE Data Engineering Bulletin
213:Resource Description Framework
1:
2506:Free software programmed in C
2291:Decision support system (DSS)
898:Stefan Manegold (June 2006).
261:. The first version under an
209:geographic information system
2481:Cross-platform free software
2317:Data Mining Extensions (DMX)
1918:Official homepage of MonetDB
1775:PVLDB Challenges and Visions
1081:"MonetDB July 2015 Released"
630:. Under development for the
201:online analytical processing
2511:Products introduced in 2004
2078:Ensemble modeling patterns
2048:Single version of the truth
887:MonetDB historic background
2537:
2432:Comparison of OLAP servers
830:"Life Sciences in MonetDB"
750:Database management system
468:Open Geospatial Consortium
215:(RDF), text retrieval and
2491:Data warehousing products
2380:
2369:
2301:Data warehouse automation
2264:
2253:
1991:
1986:Creating a data warehouse
1980:
1591:Communications of the ACM
963:. ACM. pp. 861–862.
857:Boncz, Peter (May 2002).
360:This article needs to be
64:
45:
24:
1878:. ACM. pp. 893–904.
1859:10.14778/2536274.2536297
1814:10.14778/2367502.2367535
1632:10.14778/1454159.1454227
1365:10.14778/2536274.2536297
919:10.1016/j.is.2007.05.004
2486:Cross-platform software
2327:XML for Analysis (XMLA)
1893:10.1145/2484838.2484876
1758:10.1145/2043652.2043660
1725:10.1145/1862919.1862921
1649:10.1145/1559845.1559879
1603:10.1145/1409360.1409380
1555:10.1007/3-540-45271-0_9
1429:"Embedded R in MonetDB"
1321:10.1145/2484838.2484876
1150:10.1145/1862919.1862921
1031:10.1145/2070736.2070747
969:10.1145/2213836.2213967
779:"MonetDB Release Notes"
482:. SciQL is used in the
255:University of Amsterdam
2259:Using a data warehouse
2114:Operational data store
1415:"SAM/BAM installation"
796:"GeoSpatial - MonetDB"
664:in-database processing
464:Simple Features Access
310:, integrated with the
267:Mozilla Public License
150:Mozilla Public License
56:Aug2024 (11.51) /
2276:Business intelligence
1786:. ACM. pp. 1–12.
1684:10.1007/s007780000031
2092:Focal point modeling
2064:Column-oriented DBMS
2013:Dimensional modeling
755:Column-oriented DBMS
263:open-source software
134:Column-oriented DBMS
2397:Information factory
2170:Early-arriving fact
2087:Data vault modeling
2038:Reverse star schema
1578:Proceedings of CIDR
1483:"Xquery (obsolete)"
1471:. 25 November 2015.
1469:"MonetDBLite for R"
1435:on 13 November 2014
1417:. 24 November 2014.
1222:Proceedings of CIDR
1069:. 12 December 2014.
1055:. 12 December 2014.
913:(2). ACM: 203–220.
598:data. Aimed at the
576:astronomical survey
572:virtual observatory
529:, specifically for
507:Human Brain Project
21:
2521:Structured storage
2348:Reporting software
1597:(12). ACM: 77–85.
1457:. 11 January 2015.
945:2008-05-19 at the
873:on 13 August 2011.
670:Python integration
645:module allows for
632:Linked Open Data 2
596:sequence alignment
492:2014-05-30 at the
308:Actian Corporation
217:sequence alignment
40:MonetDB Foundation
2466:Big data products
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2144:Sixth normal form
1902:978-1-4503-1921-8
1853:(12): 1286–1289.
1808:(12): 1910–1913.
1658:978-1-60558-551-2
1574:Database cracking
1564:978-3-540-41826-9
1536:. pp. 54–65.
1359:(12): 1286–1289.
1330:978-1-4503-1921-8
1218:Database cracking
1083:. 31 August 2015.
1009:ACM SIGMOD Record
978:978-1-4503-1247-9
726:extension called
722:extension, and a
710:Former extensions
618:MonetDB/RDF is a
539:Earth observation
424:Database Cracking
387:, with SciQL and
381:
380:
290:interpreter-based
251:Martin L. Kersten
172:
171:
2528:
2496:Database engines
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2033:Snowflake schema
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1672:The VLDB Journal
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1626:(2): 1553–1563.
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1236:"SIGMOD Awards"
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1193:"SIGMOD Awards"
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1174:. CWI Amsterdam
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846:. 6 March 2014.
842:
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832:. 25 July 2023.
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815:. 6 March 2014.
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798:. 25 July 2023.
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403:Query Recycling
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312:Ingres database
288:over a typical
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182:column-oriented
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1912:External links
1910:
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1887:. SSDBM. ACM.
1880:
1871:
1835:
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1797:
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1752:(4). ACM: 27.
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1315:. SSDBM. ACM.
1300:
1286:
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1227:
1208:
1184:
1163:
1144:(4). ACM: 24.
1123:
1086:
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1015:(3). ACM: 45.
992:
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724:streaming data
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600:bioinformatics
590:MonetDB has a
587:
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564:European Union
531:remote sensing
514:
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484:European Union
480:array database
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414:Martin Kersten
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1403:. 2015-09-09.
1402:
1401:"Data Vaults"
1396:
1393:
1389:. 2015-09-09.
1388:
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1112:. IEEE: 40–45
1111:
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638:R integration
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549:), MiniSEED (
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397:demand paging
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332:data sharding
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191:(CWI) in the
190:
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159:
155:
152:, version 2.0
151:
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48:
44:
41:
38:
36:
32:
28:
23:
2416:Dan Linstedt
1884:
1875:
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1801:
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1783:
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1594:
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1577:
1573:
1546:
1533:
1529:
1521:Bibliography
1508:. Retrieved
1498:
1487:. Retrieved
1477:
1463:
1449:
1437:. Retrieved
1433:the original
1423:
1409:
1395:
1381:
1356:
1352:
1339:
1312:
1289:
1280:
1260:
1254:
1243:. Retrieved
1239:
1230:
1221:
1217:
1211:
1200:. Retrieved
1196:
1187:
1176:. Retrieved
1166:
1141:
1137:
1126:
1114:. Retrieved
1109:
1075:
1061:
1047:
1012:
1008:
995:
960:
954:
934:
924:December 11,
922:. Retrieved
910:
906:
893:
868:the original
859:
852:
838:
773:
727:
713:
699:
693:
673:
654:
642:
641:
617:
589:
516:
477:
466:standard of
461:
449:
440:
427:
406:
394:
382:
369:
361:
343:Architecture
316:
301:
275:
259:Claude Monet
244:
226:
219:processing.
174:
173:
35:Developer(s)
2353:Spreadsheet
2286:Data mining
2028:Star schema
1439:12 November
700:MonetDBLite
690:MonetDBLite
649:written in
628:triplestore
513:Data Vaults
247:Peter Boncz
205:data mining
193:Netherlands
179:open-source
2460:Categories
2392:Bill Inmon
2196:Degenerate
2165:Fact table
1510:2015-05-26
1489:2015-05-26
1245:2014-12-12
1240:ACM SIGMOD
1202:2014-07-01
1197:ACM SIGMOD
1178:2009-07-01
766:References
760:Array DBMS
614:RDF/SPARQL
582:(IPHAS)
551:seismology
487:PlanetData
454:standard.
437:Components
431:ACM SIGMOD
418:ACM SIGMOD
304:VectorWise
297:CPU caches
273:standard.
106:Written in
70:Repository
2310:Languages
2296:OLAP cube
2281:Dashboard
2232:Transform
2184:Dimension
2139:Data mart
2074:Data mesh
2043:Aggregate
2008:Dimension
1867:2150-8097
1692:1066-8888
1506:. MonetDB
1485:. MonetDB
1373:2150-8097
1017:CiteSeerX
728:Data Cell
696:MonetDB.R
655:MonetDB.R
643:MonetDB/R
634:project.
610:library.
578:data for
547:astronomy
372:June 2017
286:algorithm
242:in 2009.
2425:Products
2269:Concepts
2134:Metadata
2123:Elements
2069:Data hub
2057:Variants
2003:Database
1996:Concepts
1733:52811192
1158:52811192
1116:March 6,
1053:"XQuery"
943:Archived
734:See also
608:SAMtools
490:Archived
452:SQL:2003
271:SQL:2003
232:spin-off
164:.monetdb
87:/MonetDB
81:.monetdb
58: ()
2375:Related
2227:Extract
2210:Filling
2175:Measure
1766:6707515
1700:1688757
1611:5633935
1295:"SciQL"
1039:6372175
987:9187072
592:SAM/BAM
586:SAM/BAM
568:TELEIOS
535:GeoTIFF
519:SQL/MED
498:TELEIOS
470:(OGC).
362:updated
223:History
211:(GIS),
175:MonetDB
157:Website
145:License
20:MonetDB
2385:People
1899:
1865:
1822:545154
1820:
1764:
1731:
1698:
1690:
1655:
1609:
1561:
1371:
1327:
1156:
1037:
1019:
985:
975:
716:XQuery
704:SQLite
676:Python
620:SPARQL
555:NetCDF
553:) and
527:mining
389:SPARQL
324:XQuery
197:tables
177:is an
2336:Tools
2109:ROLAP
2104:MOLAP
2099:HOLAP
1843:(PDF)
1818:S2CID
1762:S2CID
1729:S2CID
1696:S2CID
1607:S2CID
1349:(PDF)
1154:S2CID
1106:(PDF)
1035:S2CID
1005:(PDF)
983:S2CID
903:(PDF)
871:(PDF)
864:(PDF)
684:SciPy
680:NumPy
474:SciQL
293:RDBMS
138:RDBMS
89:/file
2237:Load
2158:Fact
2023:OLAP
2018:Fact
1897:ISBN
1863:ISSN
1688:ISSN
1653:ISBN
1559:ISBN
1441:2014
1369:ISSN
1325:ISBN
1118:2014
973:ISBN
926:2013
720:JAQL
647:UDFs
559:lazy
543:FITS
525:and
496:and
328:Jaql
320:APIs
278:DBMS
236:SPSS
166:.org
129:Type
83:.org
1889:doi
1855:doi
1810:doi
1754:doi
1721:doi
1680:doi
1645:doi
1628:doi
1599:doi
1551:doi
1361:doi
1317:doi
1146:doi
1027:doi
965:doi
915:doi
624:RDF
604:DNA
566:'s
541:),
458:GIS
446:SQL
410:CWI
385:SQL
282:CPU
240:IBM
229:CWI
162:www
85:/hg
79:www
2462::
1895:.
1861:.
1849:.
1845:.
1816:.
1804:.
1760:.
1750:36
1748:.
1744:.
1727:.
1717:35
1715:.
1711:.
1694:.
1686:.
1674:.
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