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DBMS > Kinetica vs. RethinkDB vs. Spark SQL vs. Splice Machine vs. SQream DB

System Properties Comparison Kinetica vs. RethinkDB vs. Spark SQL vs. Splice Machine vs. SQream DB

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonRethinkDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsDBMS for the Web with a mechanism to push updated query results to applications in realtime.Spark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Sparka GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websitewww.kinetica.comrethinkdb.comspark.apache.org/­sqlsplicemachine.comsqream.com
Technical documentationdocs.kinetica.comrethinkdb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-worksdocs.sqream.com
DeveloperKineticaThe Linux Foundation infosince July 2017Apache Software FoundationSplice MachineSQream Technologies
Initial release20122009201420142017
Current release7.1, August 20212.4.1, August 20203.5.0 ( 2.13), September 20233.1, March 20212022.1.6, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++ScalaJavaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxLinux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes infostring, binary, float, bool, date, geometryyesyesyes, ANSI Standard SQL Types
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 indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
.Net
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsnoyes infoJavauser defined functions in Python
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeClient-side triggers through changefeedsnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding inforange basedyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-document operationsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCC basedyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnonoyes
User concepts infoAccess controlAccess rights for users and roles on table levelyes infousers and table-level permissionsnoAccess rights for users, groups and roles according to SQL-standard

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More resources
KineticaRethinkDBSpark SQLSplice MachineSQream DB
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