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DBMS > Kinetica vs. PostGIS vs. Spark SQL vs. Trafodion

System Properties Comparison Kinetica vs. PostGIS vs. Spark SQL vs. Trafodion

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonPostGIS  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFully vectorized database across both GPUs and CPUsSpatial extension of PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSSpatial DBMSRelational DBMSRelational 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
Score23.90
Rank#29  Overall
#1  Spatial DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.kinetica.compostgis.netspark.apache.org/­sqltrafodion.apache.org
Technical documentationdocs.kinetica.compostgis.net/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperKineticaApache Software FoundationApache Software Foundation, originally developed by HP
Initial release2012200520142014
Current release7.1, August 20213.4.2, February 20243.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoGPL v2.0Open Source infoApache 2.0Open Source infoApache 2.0
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++CScalaC++, Java
Server operating systemsLinuxLinux
OS X
Windows
Linux
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.noyesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnoJava Stored Procedures
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes infobased on PostgreSQLyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infobased on PostgreSQLnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes
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 RAMnonono
User concepts infoAccess controlAccess rights for users and roles on table levelyes infobased on PostgreSQLnofine grained access rights according to SQL-standard

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More resources
KineticaPostGISSpark SQLTrafodion
DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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