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DBMS > Kinetica vs. RDFox vs. Spark SQL vs. STSdb

System Properties Comparison Kinetica vs. RDFox vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonRDFox  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsHigh performance knowledge graph and semantic reasoning engineSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSGraph DBMS
RDF store
Relational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score0.25
Rank#317  Overall
#26  Graph DBMS
#15  RDF stores
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.13
Rank#344  Overall
#51  Key-value stores
Websitewww.kinetica.comwww.oxfordsemantic.techspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.kinetica.comdocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaOxford Semantic TechnologiesApache Software FoundationSTS Soft SC
Initial release2012201720142011
Current release7.1, August 20216.0, Septermber 20223.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++ScalaC#
Server operating systemsLinuxLinux
macOS
Windows
Linux
OS X
Windows
Windows
Data schemeyesyes infoRDF schemasyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)
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.nono
Secondary indexesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
JDBC
ODBC
.NET Client API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
Java
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresuser defined functionsnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationreplication via a shared file systemnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlAccess rights for users and roles on table levelRoles, resources, and access typesnono

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More resources
KineticaRDFoxSpark SQLSTSdb
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