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DBMS > Citus vs. Firebase Realtime Database vs. Greenplum vs. Hazelcast vs. Sphinx

System Properties Comparison Citus vs. Firebase Realtime Database vs. Greenplum vs. Hazelcast vs. Sphinx

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGreenplum  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  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.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeRelational DBMSKey-value storeSearch engine
Secondary database modelsDocument storeDocument store
Spatial DBMS
Document store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.citusdata.comfirebase.google.com/­products/­realtime-databasegreenplum.orghazelcast.comsphinxsearch.com
Technical documentationdocs.citusdata.comfirebase.google.com/­docs/­databasedocs.greenplum.orghazelcast.org/­imdg/­docssphinxsearch.com/­docs
DeveloperGoogle infoacquired by Google 2014Pivotal Software Inc.HazelcastSphinx Technologies Inc.
Initial release20102012200520082001
Current release8.1, December 20187.0.0, September 20235.3.6, November 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC++
Server operating systemsLinuxhostedLinuxAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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 infosince Version 4.2yes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoyesSQL-like query languageSQL-like query language (SphinxQL)
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
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
JavaScript
Objective-C
C
Java
Perl
Python
R
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
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'yesyes infoEvent Listeners, Executor Servicesno
TriggersyesCallbacks are triggered when data changesyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationyes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyesno
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 ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, based on authentication and database rulesfine grained access rights according to SQL-standardRole-based access controlno

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CitusFirebase Realtime DatabaseGreenplumHazelcastSphinx
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