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DBMS > Apache IoTDB vs. Citus vs. Firebase Realtime Database vs. Kdb

System Properties Comparison Apache IoTDB vs. Citus vs. Firebase Realtime Database vs. Kdb

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCitus  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonKdb  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 PostgreSQLCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.High performance Time Series DBMS
Primary database modelTime Series DBMSRelational DBMSDocument storeTime Series DBMS
Vector DBMS
Secondary database modelsDocument storeRelational 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
Score13.60
Rank#39  Overall
#6  Document stores
Score7.73
Rank#45  Overall
#2  Time Series DBMS
#1  Vector DBMS
Websiteiotdb.apache.orgwww.citusdata.comfirebase.google.com/­products/­realtime-databasekx.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.citusdata.comfirebase.google.com/­docs/­databasecode.kx.com
DeveloperApache Software FoundationGoogle infoacquired by Google 2014Kx Systems, a division of First Derivatives plc
Initial release2018201020122000 infokdb was released 2000, kdb+ in 2003
Current release1.1.0, April 20238.1, December 20183.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availablecommercialcommercial infofree 32-bit version
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 languageJavaCq
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxhostedLinux
OS X
Solaris
Windows
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 functionalitynoyes
Secondary indexesyesyesyesyes infotable attribute 'grouped'
SQL infoSupport of SQLSQL-like query languageyes infostandard, with numerous extensionsnoSQL-like query language (q)
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
iOS
JavaScript API
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
JavaScript
Objective-C
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.limited functionality with using 'rules'user defined functions
TriggersyesyesCallbacks are triggered when data changesyes infowith views
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal 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 extensionsSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesno
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.yesnoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardyes, based on authentication and database rulesrights management via user accounts
More information provided by the system vendor
Apache IoTDBCitusFirebase Realtime DatabaseKdb
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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Apache IoTDBCitusFirebase Realtime DatabaseKdb
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