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DBMS > Apache IoTDB vs. Citus vs. Hazelcast vs. Postgres-XL

System Properties Comparison Apache IoTDB vs. Citus vs. Hazelcast vs. Postgres-XL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCitus  Xexclude from comparisonHazelcast  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkScalable 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 features
Primary database modelTime Series DBMSRelational DBMSKey-value 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
Score1.19
Rank#176  Overall
#15  Time Series DBMS
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
Websiteiotdb.apache.orgwww.citusdata.comhazelcast.comwww.postgres-xl.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.citusdata.comhazelcast.org/­imdg/­docswww.postgres-xl.org/­documentation
DeveloperApache Software FoundationHazelcast
Initial release2018201020082014 infosince 2012, originally named StormDB
Current release1.1.0, April 20238.1, December 20185.3.6, November 202310 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJavaC
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAll OS with a Java VMLinux
macOS
Data schemeyesyesschema-freeyes
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.noyes 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
SQL infoSupport of SQLSQL-like query languageyes infostandard, with numerous extensionsSQL-like query languageyes infodistributed, parallel query execution
APIs and other access methodsJDBC
Native API
ADO.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
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.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
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoEvent Listeners, Executor Servicesuser defined functions
Triggersyesyesyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication infoother methods possible by using 3rd party extensionsyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitedACID 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.yesnoyesno
User concepts infoAccess controlyesfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standard

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More resources
Apache IoTDBCitusHazelcastPostgres-XL
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