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DBMS > Kinetica vs. OpenEdge vs. Splice Machine

System Properties Comparison Kinetica vs. OpenEdge vs. Splice Machine

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonOpenEdge  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsApplication development environment with integrated database management systemOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSRelational DBMS
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
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.kinetica.comwww.progress.com/­openedgesplicemachine.com
Technical documentationdocs.kinetica.comdocumentation.progress.com/­output/­ua/­OpenEdge_latestsplicemachine.com/­how-it-works
DeveloperKineticaProgress Software CorporationSplice Machine
Initial release201219842014
Current release7.1, August 2021OpenEdge 12.2, March 20203.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++Java
Server operating systemsLinuxAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyes
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoclose to SQL 92yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Progress proprietary ABL (Advanced Business Language)C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyesyes infoJava
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infosince Version 11.4Shared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
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 levelUsers and groupsAccess rights for users, groups and roles according to SQL-standard

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More resources
KineticaOpenEdgeSplice Machine
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