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DBMS > Kinetica vs. OceanBase vs. Spark SQL vs. Stardog

System Properties Comparison Kinetica vs. OceanBase vs. Spark SQL vs. Stardog

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonOceanBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA distributed, high available RDBMS compatible with Oracle and MySQLSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSRelational DBMSRelational DBMSGraph DBMS
RDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score1.57
Rank#149  Overall
#69  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.kinetica.comen.oceanbase.comspark.apache.org/­sqlwww.stardog.com
Technical documentationdocs.kinetica.comen.oceanbase.com/­docs/­oceanbase-databasespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperKineticaOceanBase infopreviously Alibaba and Ant GroupApache Software FoundationStardog-Union
Initial release2012201020142010
Current release7.1, August 20214.3.0, April 20243.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoCommercial license availableOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
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++ScalaJava
Server operating systemsLinuxLinuxLinux
OS X
Windows
Linux
macOS
Windows
Data schemeyesyesyesschema-free and OWL/RDFS-schema support
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.noyesnono infoImport/export of XML data possible
Secondary indexesyesyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsPL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible modenouser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by hash, key, range, range columns, list, and list columns)yes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesyesnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standardnoAccess rights for users and roles

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KineticaOceanBaseSpark SQLStardog
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