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DBMS > MonetDB vs. RDF4J

System Properties Comparison MonetDB vs. RDF4J

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Editorial information provided by DB-Engines
NameMonetDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA relational database management system that stores data in columnsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSRDF store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.94
Rank#112  Overall
#59  Relational DBMS
Score0.39
Rank#217  Overall
#11  RDF stores
Websitewww.monetdb.orgrdf4j.org
Technical documentationwww.monetdb.org/­Documentationdocs.rdf4j.org
DeveloperMonetDB BVSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20042004
Current releaseAug2018-SP2, January 2019
License infoCommercial or Open SourceOpen Source infoMozilla Public License 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava
Server operating systemsFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
Data schemeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes
Secondary indexesyesyes
SQL infoSupport of SQLyes infoSQL 2003 with some extensionsno
APIs and other access methodsnative C library infoMAPI library (MonetDB application programming interface)
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresyes, in SQL, C, Ryes
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding via remote tablesnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoMaster-slave replication available in experimental statusnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infoin-memory storage is supported as well
User concepts infoAccess controlfine grained access rights according to SQL-standardno
More information provided by the system vendor
MonetDBRDF4J infoformerly known as Sesame
Specific characteristicsColumn-store In-memory optimized GeoSpatial support JSON document support
» more
Competitive advantagesScalable architecture - vertical data organization and in-memory optimization guarantee...
» more
Typical application scenariosAnalytical database, Data warehouse, OLAP Data mining Scientific database
» more
Key customersNumascale , Spinque , SecurActive , CHS , NOZHUP
» more
Licensing and pricing modelsFree and open-source software, Mozilla Public License 2.0 Commercial support available
» more
News

Combined insert, updates and deletes with merge statements
8 March 2019

Updatable merge tables with partition predicates
26 February 2019

Remote Tables and Authorization
10 August 2018

IoT and streaming in MonetDB
26 July 2018

JIT C/C++ UDFs in MonetDB
23 May 2018

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
MonetDBRDF4J infoformerly known as Sesame
Recent citations in the news

Mark Raasveldt wins Student Research Competition at SIGMOD 2018
22 June 2018, Centrum Wiskunde & Informatica (CWI)

Numascale Works with MonetDB to Extend the NumaQ In-Memory Analytics Offering
16 February 2015, EnterpriseTech

CWI spin-off company Dataspex offers solutions to big data challenges in astronomy
12 March 2019, Centrum Wiskunde & Informatica (CWI)

Columnar Databases and Vectorization
27 May 2018, InfoQ.com

1st International Conference on Big Scientific Data Management (BigSDM2018)
30 November 2018, Centrum Wiskunde & Informatica (CWI)

provided by Google News

Ontotext's GraphDB 8.9 Boosts Semantic Similarity Search
10 April 2019, PRNewswire

provided by Google News

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