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

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

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHazelcast  Xexclude from comparisonHBase  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA widely adopted in-memory data gridWide-column store based on Apache Hadoop and on concepts of BigTableBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSKey-value storeWide column storeRelational DBMS
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
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitewww.citusdata.comhazelcast.comhbase.apache.orgwww.postgres-xl.org
Technical documentationdocs.citusdata.comhazelcast.org/­imdg/­docshbase.apache.org/­book.htmlwww.postgres-xl.org/­documentation
DeveloperHazelcastApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2010200820082014 infosince 2012, originally named StormDB
Current release8.1, December 20185.3.6, November 20232.3.4, January 202110 R1, October 2018
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache version 2Open Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaJavaC
Server operating systemsLinuxAll OS with a Java VMLinux
Unix
Windows infousing Cygwin
Linux
macOS
Data schemeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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 strategynoyes infoXML type, but no XML query functionality
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like query languagenoyes infodistributed, parallel query execution
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
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 Servicesyes infoCoprocessors in Javauser defined functions
Triggersyesyes infoEventsyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoReplicated MapMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedSingle row ACID (across millions of columns)ACID infoMVCC
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.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard

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More resources
CitusHazelcastHBasePostgres-XL
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