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DBMS > Kinetica vs. PostgreSQL vs. Snowflake vs. Spark SQL vs. SQream DB

System Properties Comparison Kinetica vs. PostgreSQL vs. Snowflake vs. Spark SQL vs. SQream DB

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSnowflake  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  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 SQLCloud-based data warehousing service for structured and semi-structured dataSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloads
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.Relational DBMSRelational DBMSRelational 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
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score634.91
Rank#4  Overall
#4  Relational DBMS
Score125.38
Rank#9  Overall
#6  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.72
Rank#235  Overall
#108  Relational DBMS
Websitewww.kinetica.comwww.postgresql.orgwww.snowflake.comspark.apache.org/­sqlsqream.com
Technical documentationdocs.kinetica.comwww.postgresql.org/­docsdocs.snowflake.net/­manuals/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperKineticaPostgreSQL Global Development Group infowww.postgresql.org/­developerSnowflake Computing Inc.Apache Software FoundationSQream Technologies
Initial release20121989 info1989: Postgres, 1996: PostgreSQL201420142017
Current release7.1, August 202116.2, February 20243.5.0 ( 2.13), September 20232022.1.6, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoBSDcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
Implementation languageC, C++CScalaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
hostedLinux
OS X
Windows
Linux
Data schemeyesyesyes infosupport of semi-structured data formats (JSON, XML, Avro)yesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes, ANSI Standard SQL Types
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.yesno
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard with numerous extensionsyesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
CLI Client
JDBC
ODBC
JDBC
ODBC
.Net
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functionsnouser defined functions in Python
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno infosimilar concept for controling cloud resourcesnono
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and (since PostgreSQL 11) by hashyesyes, utilizing Spark Corehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnonono
User concepts infoAccess controlAccess rights for users and roles on table levelfine grained access rights according to SQL-standardUsers with fine-grained authorization concept, user roles and pluggable authenticationno

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More resources
KineticaPostgreSQLSnowflakeSpark SQLSQream DB
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