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DBMS > Kinetica vs. RDFox vs. Spark SQL

System Properties Comparison Kinetica vs. RDFox vs. Spark SQL

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonRDFox  Xexclude from comparisonSpark SQL  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 processing
Primary database modelRelational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.24
Rank#309  Overall
#25  Graph DBMS
#14  RDF stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.kinetica.comwww.oxfordsemantic.techspark.apache.org/­sql
Technical documentationdocs.kinetica.comdocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaOxford Semantic TechnologiesApache Software Foundation
Initial release201220172014
Current release7.1, August 20216.0, Septermber 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++Scala
Server operating systemsLinuxLinux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
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 methodsno
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 integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes
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 typesno

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More resources
KineticaRDFoxSpark SQL
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