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

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

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonOpenEdge  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsApplication development environment with integrated database management systemSpark 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 DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitewww.kinetica.comwww.progress.com/­openedgespark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.kinetica.comdocumentation.progress.com/­output/­ua/­OpenEdge_latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaProgress Software CorporationApache Software FoundationSTS Soft SC
Initial release2012198420142011
Current release7.1, August 2021OpenEdge 12.2, March 20203.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen 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++ScalaC#
Server operating systemsLinuxAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes 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.noyesno
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoclose to SQL 92SQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
.NET Client API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Progress proprietary ABL (Advanced Business Language)Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresuser defined functionsyesnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infosince Version 11.4yes, 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 configurationImmediate Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
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 levelUsers and groupsnono

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More resources
KineticaOpenEdgeSpark SQLSTSdb
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