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DBMS > Kinetica vs. Sequoiadb vs. Spark SQL vs. STSdb

System Properties Comparison Kinetica vs. Sequoiadb vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score0.50
Rank#264  Overall
#42  Document stores
#121  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.13
Rank#344  Overall
#51  Key-value stores
Websitewww.kinetica.comwww.sequoiadb.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.kinetica.comwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaSequoiadb Ltd.Apache Software FoundationSTS Soft SC
Initial release2012201320142011
Current release7.1, August 20213.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++ScalaC#
Server operating systemsLinuxLinuxLinux
OS X
Windows
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infooid, date, timestamp, binary, regexyesyes infoprimitive types and user defined types (classes)
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 indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
proprietary protocol using JSONJDBC
ODBC
.NET Client API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresuser defined functionsJavaScriptnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationnonenone
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 Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoDocument is locked during a transactionnono
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 RAMnono
User concepts infoAccess controlAccess rights for users and roles on table levelsimple password-based access controlnono

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More resources
KineticaSequoiadbSpark SQLSTSdb
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