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DBMS > Citus vs. Hive vs. Solr vs. Sphinx vs. Splice Machine

System Properties Comparison Citus vs. Hive vs. Solr vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHive  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLdata warehouse software for querying and managing large distributed datasets, built on HadoopA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSSearch engineSearch engineRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.citusdata.comhive.apache.orgsolr.apache.orgsphinxsearch.comsplicemachine.com
Technical documentationdocs.citusdata.comcwiki.apache.org/­confluence/­display/­Hive/­Homesolr.apache.org/­resources.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software FoundationSphinx Technologies Inc.Splice Machine
Initial release20102012200620012014
Current release8.1, December 20183.1.3, April 20229.6.1, May 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2Open Source infoApache Version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaJavaC++Java
Server operating systemsLinuxAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingnoyes
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 functionalityyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like DML and DDL statementsSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)yes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Thrift
Java API
RESTful HTTP/JSON API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infouser defined functions and integration of map-reduceJava pluginsnoyes infoJava
Triggersyesnoyes infoUser configurable commands triggered on index changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsselectable replication factoryesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducespark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesyesnoAccess rights for users, groups and roles according to SQL-standard

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CitusHiveSolrSphinxSplice Machine
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