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DBMS > Kinetica vs. Spark SQL vs. Splice Machine vs. Transbase

System Properties Comparison Kinetica vs. Spark SQL vs. Splice Machine vs. Transbase

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsSpark 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 resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.kinetica.comspark.apache.org/­sqlsplicemachine.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-workswww.transaction.de/­en/­products/­transbase/­features.html
DeveloperKineticaApache Software FoundationSplice MachineTransaction Software GmbH
Initial release2012201420141987
Current release7.1, August 20213.5.0 ( 2.13), September 20233.1, March 2021Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availablecommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ScalaJavaC and C++
Server operating systemsLinuxLinux
OS X
Windows
Linux
OS X
Solaris
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyesyes
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 indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnoyes infoJavayes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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 RAMnoyesno
User concepts infoAccess controlAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
KineticaSpark SQLSplice MachineTransbase
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