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DBMS > Kinetica vs. Postgres-XL vs. SingleStore

System Properties Comparison Kinetica vs. Postgres-XL vs. SingleStore

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresMySQL 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 DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#202  Overall
#97  Relational DBMS
Score0.72
Rank#204  Overall
#99  Relational DBMS
Score6.66
Rank#59  Overall
#33  Relational DBMS
Websitewww.kinetica.comwww.postgres-xl.orgwww.singlestore.com
Technical documentationwww.kinetica.com/­docswww.postgres-xl.org/­documentationdocs.singlestore.com
DeveloperKineticaSingleStore Inc.
Initial release20122014 infosince 2012, originally named StormDB2013
Current release7.1, August 202110 R1, October 20187.6, November 2021
License infoCommercial or Open SourcecommercialOpen Source infoMozilla public licensecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStore Managed Service: 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++CC++, Go
Server operating systemsLinuxLinux
macOS
Linux info64 bit version required
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 infoXML type, but no XML query functionalityno
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infodistributed, parallel query executionyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono 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 datanoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes 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 levelfine grained access rights according to SQL-standardFine grained access control via users, groups and roles
More information provided by the system vendor
KineticaPostgres-XLSingleStore infoformer name was MemSQL
Specific characteristicsNative and fully vectorized database across both GPUs and CPUs, with memory first...
» more
SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesBest in class geospatial and temporal analytics. Lockless architecture provides real-time...
» more
SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosAny application requiring (1) real time insights, (2) time series analysis (3) geospatial...
» more
Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersCitibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more
IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsThe largest IoT deployment in the world, NORAD, runs on Kinetica.
» more
Customers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsAlways Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
» more
F ree Tier and Enterprise Edition
» more

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More resources
KineticaPostgres-XLSingleStore infoformer name was MemSQL
Conferences and events

Turbocharge Your Open-Source DB to Drive 100x Faster Performance
Webinar, 10am PT, 18 January 2022

Recent citations in the news

Bank Replaces Hundreds of Spark Streaming Nodes with Kinetica
6 January 2022, Datanami

GPU Database Market is Going to Boom: Major Giants | Kinetica, OmniSci, SQream, Neo4j – Industrial IT
14 January 2022, Industrial IT

The Global GPU Database Market is expected to grow by $ 361.56 mn during 2021-2025, progressing at a CAGR of 17.82% during the forecast period
21 December 2021, Yahoo Finance

Kinetica Now Accessible as a Service on Microsoft Azure
14 October 2021, HPCwire

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14 April 2019, Packt Hub

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8 September 2021, TechCrunch

Database startup SingleStore raises $80M
8 September 2021, VentureBeat

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13 January 2022, Solutions Review

SingleStore says it's the world's first database to support analytical and transactional workloads
23 June 2021, SiliconANGLE News

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17 December 2021, Datanami

provided by Google News

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