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DBMS > Citus vs. Hazelcast vs. Postgres-XL vs. Sphinx

System Properties Comparison Citus vs. Hazelcast vs. Postgres-XL vs. Sphinx

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHazelcast  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA widely adopted in-memory data gridBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSKey-value storeRelational DBMSSearch engine
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Score0.52
Rank#256  Overall
#117  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitewww.citusdata.comhazelcast.comwww.postgres-xl.orgsphinxsearch.com
Technical documentationdocs.citusdata.comhazelcast.org/­imdg/­docswww.postgres-xl.org/­documentationsphinxsearch.com/­docs
DeveloperHazelcastSphinx Technologies Inc.
Initial release201020082014 infosince 2012, originally named StormDB2001
Current release8.1, December 20185.3.6, November 202310 R1, October 20183.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoMozilla public licenseOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaCC++
Server operating systemsLinuxAll OS with a Java VMLinux
macOS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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 functionalityyes infothe object must implement a serialization strategyyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like query languageyes infodistributed, parallel query executionSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
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.yes infoEvent Listeners, Executor Servicesuser defined functionsno
Triggersyesyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACID infoMVCCno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standardno

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CitusHazelcastPostgres-XLSphinx
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