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DBMS > EDB Postgres vs. Kinetica vs. Postgres-XL vs. Spark SQL vs. Sphinx

System Properties Comparison EDB Postgres vs. Kinetica vs. Postgres-XL vs. Spark SQL vs. Sphinx

Editorial information provided by DB-Engines
NameEDB Postgres  Xexclude from comparisonKinetica  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Fully vectorized database across both GPUs and CPUsBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#130  Overall
#60  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.enterprisedb.comwww.kinetica.comwww.postgres-xl.orgspark.apache.org/­sqlsphinxsearch.com
Technical documentationwww.enterprisedb.com/­docsdocs.kinetica.comwww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperEnterpriseDBKineticaApache Software FoundationSphinx Technologies Inc.
Initial release200520122014 infosince 2012, originally named StormDB20142001
Current release14, December 20217.1, August 202110 R1, October 20183.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercial infoBSD for PostgreSQL-componentscommercialOpen Source infoMozilla public licenseOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC, C++CScalaC++
Server operating systemsLinux
Windows
LinuxLinux
macOS
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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 functionality.noyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard with numerous extensionsSQL-like DML and DDL statementsyes infodistributed, parallel query executionSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functionsuser defined functionsnono
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoby hash, list or rangeShardinghorizontal partitioningyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoMVCCnono
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 levelfine grained access rights according to SQL-standardnono

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More resources
EDB PostgresKineticaPostgres-XLSpark SQLSphinx
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