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DBMS > Citus vs. Firebase Realtime Database vs. FoundationDB vs. Kinetica vs. Linter

System Properties Comparison Citus vs. Firebase Realtime Database vs. FoundationDB vs. Kinetica vs. Linter

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonFoundationDB  Xexclude from comparisonKinetica  Xexclude from comparisonLinter  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionScalable 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.Ordered key-value store. Core features are complimented by layers.Fully vectorized database across both GPUs and CPUsRDBMS for high security requirements
Primary database modelRelational DBMSDocument storeDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Websitewww.citusdata.comfirebase.google.com/­products/­realtime-databasegithub.com/­apple/­foundationdbwww.kinetica.comlinter.ru
Technical documentationdocs.citusdata.comfirebase.google.com/­docs/­databaseapple.github.io/­foundationdbdocs.kinetica.com
DeveloperGoogle infoacquired by Google 2014FoundationDBKineticarelex.ru
Initial release20102012201320121990
Current release8.1, December 20186.2.28, November 20207.1, August 2021
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++C, C++C and C++
Server operating systemsLinuxhostedLinux
OS X
Windows
LinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesschema-freeschema-free infosome layers support schemasyesyes
Typing infopredefined data types such as float or dateyesyesno infosome layers support typingyesyes
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 functionalitynonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnosupported in specific SQL layer onlySQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
JavaScript
Objective-C
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.limited functionality with using 'rules'in SQL-layer onlyuser defined functionsyes infoproprietary syntax with the possibility to convert from PL/SQL
TriggersyesCallbacks are triggered when data changesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Linearizable consistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoin SQL-layer onlyyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, based on authentication and database rulesnoAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
CitusFirebase Realtime DatabaseFoundationDBKineticaLinter
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