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DBMS > Databricks vs. MonetDB vs. RDF4J

System Properties Comparison Databricks vs. MonetDB vs. RDF4J

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMonetDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A 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 modelDocument store
Relational DBMS
Relational DBMSRDF store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.databricks.comwww.monetdb.orgrdf4j.org
Technical documentationdocs.databricks.comwww.monetdb.org/­Documentationrdf4j.org/­documentation
DeveloperDatabricksMonetDB BVSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release201320042004
Current releaseDec2023 (11.49), December 2023
License infoCommercial or Open SourcecommercialOpen Source infoMozilla Public License 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava
Server operating systemshostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yes
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infoSQL 2003 with some extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesPython
R
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes, 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 nodesyesnone infoSource-replica replication available in experimental statusnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlfine grained access rights according to SQL-standardno
More information provided by the system vendor
DatabricksMonetDBRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksMonetDBRDF4J infoformerly known as Sesame
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