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DBMS > Kinetica vs. Rockset vs. Spark SQL vs. SQL.JS

System Properties Comparison Kinetica vs. Rockset vs. Spark SQL vs. SQL.JS

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQL.JS  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processingPort of SQLite to JavaScript
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.53
Rank#252  Overall
#116  Relational DBMS
Websitewww.kinetica.comrockset.comspark.apache.org/­sqlsql.js.org
Technical documentationdocs.kinetica.comdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsql.js.org/­documentation/­index.html
DeveloperKineticaRocksetApache Software FoundationAlon Zakai infoenhancements implemented by others
Initial release2012201920142012
Current release7.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++ScalaJavaScript
Server operating systemsLinuxhostedLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesdynamic typingyesyes
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.nono infoingestion from XML files supportednono
Secondary indexesyesall fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statementsRead-only SQL queries, including JOINsSQL-like DML and DDL statementsyes infoSQL-92 is not fully supported
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTJDBC
ODBC
JavaScript API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresuser defined functionsnonono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenonono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnonenone
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 configurationEventual Consistencynone
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesno infoexcept by serializing a db to a file
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights for users and organizations can be defined via Rockset consolenono

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More resources
KineticaRocksetSpark SQLSQL.JS
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