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DBMS > Kinetica vs. PostGIS vs. RDF4J vs. SingleStore

System Properties Comparison Kinetica vs. PostGIS vs. RDF4J vs. SingleStore

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonPostGIS  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsSpatial extension of PostgreSQLRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelRelational DBMSSpatial DBMSRDF storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMSDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score21.72
Rank#29  Overall
#1  Spatial DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score5.38
Rank#62  Overall
#35  Relational DBMS
Websitewww.kinetica.compostgis.netrdf4j.orgwww.singlestore.com
Technical documentationdocs.kinetica.compostgis.net/­documentationrdf4j.org/­documentationdocs.singlestore.com
DeveloperKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SingleStore Inc.
Initial release2012200520042013
Current release7.1, August 20213.4.2, February 20248.5, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoGPL v2.0Open Source infoEclipse Distribution License (EDL), v1.0.commercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageC, C++CJavaC++, Go
Server operating systemsLinuxLinux
OS X
Unix
Windows
Linux info64 bit version required
Data schemeyesyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsyesyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infobased on PostgreSQLnoneSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infobased on PostgreSQLnoneSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
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 levelyes infobased on PostgreSQLnoFine grained access control via users, groups and roles
More information provided by the system vendor
KineticaPostGISRDF4J infoformerly known as SesameSingleStore infoformer name was MemSQL
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
KineticaPostGISRDF4J infoformerly known as SesameSingleStore infoformer name was MemSQL
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