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DBMS > Kinetica vs. Spark SQL vs. SpatiaLite vs. Transbase

System Properties Comparison Kinetica vs. Spark SQL vs. SpatiaLite vs. Transbase

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonSpatiaLite  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 processingSpatial extension of SQLiteA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSSpatial DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.63
Rank#146  Overall
#3  Spatial DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.kinetica.comspark.apache.org/­sqlwww.gaia-gis.it/­fossil/­libspatialite/­indexwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.gaia-gis.it/­gaia-sins/­spatialite_topics.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperKineticaApache Software FoundationAlessandro FurieriTransaction Software GmbH
Initial release2012201420081987
Current release7.1, August 20213.5.0 ( 2.13), September 20235.0.0, August 2020Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoMPL 1.1, GPL v2.0 or LGPL v2.1commercial 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++ScalaC++C and C++
Server operating systemsLinuxLinux
OS X
Windows
server-lessFreeBSD
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.nononono
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
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnonoyes
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 Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneSource-replica replication
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 Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDyes
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 RAMnoyesno
User concepts infoAccess controlAccess rights for users and roles on table levelnonofine grained access rights according to SQL-standard

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More resources
KineticaSpark SQLSpatiaLiteTransbase
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