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DBMS > Citus vs. GridDB vs. Hazelcast vs. TimescaleDB

System Properties Comparison Citus vs. GridDB vs. Hazelcast vs. TimescaleDB

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLScalable in-memory time series database optimized for IoT and Big DataA widely adopted in-memory data gridA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSTime Series DBMSKey-value storeTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.citusdata.comgriddb.nethazelcast.comwww.timescale.com
Technical documentationdocs.citusdata.comdocs.griddb.nethazelcast.org/­imdg/­docsdocs.timescale.com
DeveloperToshiba CorporationHazelcastTimescale
Initial release2010201320082017
Current release8.1, December 20185.1, August 20225.3.6, November 20232.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0
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 languageCC++JavaC
Server operating systemsLinuxLinuxAll OS with a Java VMLinux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 functionalitynoyes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
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
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoEvent Listeners, Executor Servicesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyesyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationyes infoReplicated MapSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelone or two-phase-commit; repeatable reads; read commitedACID
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-standardAccess rights for users can be defined per databaseRole-based access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
CitusGridDBHazelcastTimescaleDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
CitusGridDBHazelcastTimescaleDB
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