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DBMS > Citus vs. Hazelcast vs. Microsoft Azure Table Storage vs. Percona Server for MongoDB

System Properties Comparison Citus vs. Hazelcast vs. Microsoft Azure Table Storage vs. Percona Server for MongoDB

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA widely adopted in-memory data gridA Wide Column Store for rapid development using massive semi-structured datasetsA drop-in replacement for MongoDB Community Edition with enterprise-grade features.
Primary database modelRelational DBMSKey-value storeWide column storeDocument store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.13
Rank#117  Overall
#56  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Score0.50
Rank#250  Overall
#39  Document stores
Websitewww.citusdata.comhazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.percona.com/­mongodb/­software/­percona-server-for-mongodb
Technical documentationdocs.citusdata.comhazelcast.org/­imdg/­docsdocs.percona.com/­percona-distribution-for-mongodb
DeveloperHazelcastMicrosoftPercona
Initial release2010200820122015
Current release8.1, December 20185.3.6, November 20233.4.10-2.10, November 2017
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoGPL Version 2
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 languageCJavaC++
Server operating systemsLinuxAll OS with a Java VMhostedLinux
Data schemeyesschema-freeschema-freeschema-free
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 functionalityyes infothe object must implement a serialization strategynono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like query languagenono
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIproprietary protocol using JSON
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++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
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 ServicesnoJavaScript
Triggersyesyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoReplicated Mapyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedoptimistic 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.noyesnoyes infovia In-Memory Engine
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlAccess rights based on private key authentication or shared access signaturesAccess rights for users and roles

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More resources
CitusHazelcastMicrosoft Azure Table StoragePercona Server for MongoDB
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