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DBMS > Kinetica vs. Postgres-XL vs. Splice Machine vs. TimesTen

System Properties Comparison Kinetica vs. Postgres-XL vs. Splice Machine vs. TimesTen

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.kinetica.comwww.postgres-xl.orgsplicemachine.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.kinetica.comwww.postgres-xl.org/­documentationsplicemachine.com/­how-it-worksdocs.oracle.com/­database/­timesten-18.1
DeveloperKineticaSplice MachineOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20122014 infosince 2012, originally named StormDB20141998
Current release7.1, August 202110 R1, October 20183.1, March 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialOpen Source infoMozilla public licenseOpen Source infoAGPL 3.0, commercial license availablecommercial
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++CJava
Server operating systemsLinuxLinux
macOS
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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.noyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infodistributed, parallel query executionyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsyes infoJavaPL/SQL
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoMVCCACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyesyes
User concepts infoAccess controlAccess rights for users and roles on table levelfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
KineticaPostgres-XLSplice MachineTimesTen
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