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DBMS > Kinetica vs. Microsoft Azure SQL Database vs. PostGIS vs. Spark SQL

System Properties Comparison Kinetica vs. Microsoft Azure SQL Database vs. PostGIS vs. Spark SQL

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonPostGIS  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerSpatial extension of PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSSpatial DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasepostgis.netspark.apache.org/­sql
Technical documentationdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlpostgis.net/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaMicrosoftApache Software Foundation
Initial release2012201020052014
Current release7.1, August 2021V123.4.2, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL v2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++CScala
Server operating systemsLinuxhostedLinux
OS X
Windows
Data schemeyesyesyesyes
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.noyesyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsTransact SQLuser defined functionsno
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 PostgreSQLyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, with always 3 replicas availableyes infobased on PostgreSQLnone
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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 levelfine grained access rights according to SQL-standardyes infobased on PostgreSQLno

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More resources
KineticaMicrosoft Azure SQL Database infoformerly SQL AzurePostGISSpark SQL
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