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DBMS > Kinetica vs. PostgreSQL vs. Riak KV vs. Splice Machine

System Properties Comparison Kinetica vs. PostgreSQL vs. Riak KV vs. Splice Machine

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonPostgreSQL  Xexclude from comparisonRiak KV  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLDistributed, fault tolerant key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Key-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.kinetica.comwww.postgresql.orgsplicemachine.com
Technical documentationdocs.kinetica.comwww.postgresql.org/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestsplicemachine.com/­how-it-works
DeveloperKineticaPostgreSQL Global Development Group infowww.postgresql.org/­developerOpenSource, formerly Basho TechnologiesSplice Machine
Initial release20121989 info1989: Postgres, 1996: PostgreSQL20092014
Current release7.1, August 202116.3, May 20243.2.0, December 20223.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoApache version 2, commercial enterprise editionOpen Source infoAGPL 3.0, 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++CErlangJava
Server operating systemsLinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesrestrictedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard with numerous extensionsnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Native Erlang Interface
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Erlangyes infoJava
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and (since PostgreSQL 11) by hashSharding infono "single point of failure"Shared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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 RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelfine grained access rights according to SQL-standardyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standard

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KineticaPostgreSQLRiak KVSplice Machine
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