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DBMS > Citus vs. Kinetica vs. Microsoft Azure Table Storage vs. Spark SQL

System Properties Comparison Citus vs. Kinetica vs. Microsoft Azure Table Storage vs. Spark SQL

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSWide column storeRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.citusdata.comwww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sql
Technical documentationdocs.citusdata.comdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaMicrosoftApache Software Foundation
Initial release2010201220122014
Current release8.1, December 20187.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC, C++Scala
Server operating systemsLinuxLinuxhostedLinux
OS X
Windows
Data schemeyesyesschema-freeyes
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.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyesnono
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functionsnono
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingno
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.noyes infoGPU vRAM or System RAMnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signaturesno

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CitusKineticaMicrosoft Azure Table StorageSpark SQL
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