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DBMS > Apache IoTDB vs. Citus vs. GridDB vs. SiteWhere

System Properties Comparison Apache IoTDB vs. Citus vs. GridDB vs. SiteWhere

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCitus  Xexclude from comparisonGridDB  Xexclude from comparisonSiteWhere  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 PostgreSQLScalable in-memory time series database optimized for IoT and Big DataM2M integration platform for persisting/querying time series data
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score2.13
Rank#117  Overall
#56  Relational DBMS
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score0.07
Rank#347  Overall
#33  Time Series DBMS
Websiteiotdb.apache.orgwww.citusdata.comgriddb.netgithub.com/­sitewhere/­sitewhere
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.citusdata.comdocs.griddb.netsitewhere1.sitewhere.io/­index.html
DeveloperApache Software FoundationToshiba CorporationSiteWhere
Initial release2018201020132010
Current release1.1.0, April 20238.1, December 20185.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open 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 infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinuxLinux
OS X
Windows
Data schemeyesyesyespredefined scheme
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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 functionalitynono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageyes infostandard, with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyesyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding infobased on HBase
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 extensionsSource-replica replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelno
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-standardAccess rights for users can be defined per databaseUsers with fine-grained authorization concept

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More resources
Apache IoTDBCitusGridDBSiteWhere
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