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DBMS > Citus vs. Firebase Realtime Database vs. Hazelcast vs. Microsoft Azure Data Explorer vs. RavenDB

System Properties Comparison Citus vs. Firebase Realtime Database vs. Hazelcast vs. Microsoft Azure Data Explorer vs. RavenDB

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  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 gridFully managed big data interactive analytics platformOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSDocument storeKey-value storeRelational DBMS infocolumn orientedDocument store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Graph 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
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score3.01
Rank#101  Overall
#17  Document stores
Websitewww.citusdata.comfirebase.google.com/­products/­realtime-databasehazelcast.comazure.microsoft.com/­services/­data-explorerravendb.net
Technical documentationdocs.citusdata.comfirebase.google.com/­docs/­databasehazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerravendb.net/­docs
DeveloperGoogle infoacquired by Google 2014HazelcastMicrosoftHibernating Rhinos
Initial release20102012200820192010
Current release8.1, December 20185.3.6, November 2023cloud service with continuous releases5.4, July 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
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 VMhostedLinux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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 indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-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
Microsoft SQL Server communication protocol (MS-TDS)
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
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.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, possible languages: KQL, Python, Ryes
TriggersyesCallbacks are triggered when data changesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
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 AlgorithmEventual Consistency
Immediate Consistency
Default 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 integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesone or two-phase-commit; repeatable reads; read commitednoACID, Cluster-wide transaction available
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, based on authentication and database rulesRole-based access controlAzure Active Directory AuthenticationAuthorization levels configured per client per database

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CitusFirebase Realtime DatabaseHazelcastMicrosoft Azure Data ExplorerRavenDB
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