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DBMS > Citus vs. Firebase Realtime Database vs. Hazelcast vs. RavenDB

System Properties Comparison Citus vs. Firebase Realtime Database vs. Hazelcast vs. RavenDB

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHazelcast  Xexclude from comparisonRavenDB  Xexclude from comparison
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.A widely adopted in-memory data gridOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSDocument storeKey-value storeDocument store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score15.00
Rank#39  Overall
#6  Document stores
Score6.87
Rank#55  Overall
#6  Key-value stores
Score3.01
Rank#101  Overall
#17  Document stores
Websitewww.citusdata.comfirebase.google.com/­products/­realtime-databasehazelcast.comravendb.net
Technical documentationdocs.citusdata.comfirebase.google.com/­docs/­databasehazelcast.org/­imdg/­docsravendb.net/­docs
DeveloperGoogle infoacquired by Google 2014HazelcastHibernating Rhinos
Initial release2010201220082010
Current release8.1, December 20185.3.6, November 20235.4, July 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC#
Server operating systemsLinuxhostedAll OS with a Java VMLinux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSQL-like query languageSQL-like query language (RQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
JavaScript
Objective-C
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
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'yes infoEvent Listeners, Executor Servicesyes
TriggersyesCallbacks are triggered when data changesyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoReplicated MapMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesone or two-phase-commit; repeatable reads; read commitedACID, Cluster-wide transaction available
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.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, based on authentication and database rulesRole-based access controlAuthorization levels configured per client per database

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More resources
CitusFirebase Realtime DatabaseHazelcastRavenDB
DB-Engines blog posts

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