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

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

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonRDFox  Xexclude from comparisonSpark SQL  Xexclude from comparisonVelocityDB  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 processingA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelRelational DBMSGraph DBMS
RDF store
Relational DBMSGraph DBMS
Object oriented DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websitewww.kinetica.comwww.oxfordsemantic.techspark.apache.org/­sqlvelocitydb.com
Technical documentationdocs.kinetica.comdocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvelocitydb.com/­UserGuide
DeveloperKineticaOxford Semantic TechnologiesApache Software FoundationVelocityDB Inc
Initial release2012201720142011
Current release7.1, August 20216.0, Septermber 20223.5.0 ( 2.13), September 20237.x
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++ScalaC#
Server operating systemsLinuxLinux
macOS
Windows
Linux
OS X
Windows
Any that supports .NET
Data schemeyesyes infoRDF schemasyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesnoyes
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
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
Java
Java
Python
R
Scala
.Net
Server-side scripts infoStored proceduresuser defined functionsnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationreplication via a shared file systemnone
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 setupsImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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 RAMyesnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelRoles, resources, and access typesnoBased on Windows Authentication

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More resources
KineticaRDFoxSpark SQLVelocityDB
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