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DBMS > Solr vs. Sphinx vs. Splice Machine vs. UniData,UniVerse

System Properties Comparison Solr vs. Sphinx vs. Splice Machine vs. UniData,UniVerse

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Editorial information provided by DB-Engines
NameSolr  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionA 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 SparkMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelSearch engineSearch engineRelational DBMSMultivalue DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websitesolr.apache.orgsphinxsearch.comsplicemachine.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationsolr.apache.org/­resources.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-worksdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperApache Software FoundationSphinx Technologies Inc.Splice MachineRocket Software
Initial release2006200120141985
Current release9.5.0, February 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaC
Server operating systemsAll 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
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyesschema-free
Typing infopredefined data types such as float or dateyes infosupports customizable data types and automatic typingnoyesoptional
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
Secondary indexesyes infoAll search fields are automatically indexedyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)yesyes
APIs and other access methodsJava API
RESTful HTTP/JSON API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languages.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
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresJava pluginsnoyes infoJavayes
Triggersyes infoUser configurable commands triggered on index changesnoyesyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnoACIDACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlyesnoAccess rights for users, groups and roles according to SQL-standardAccess rights according to SQL-standard and operating system based

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More resources
SolrSphinxSplice MachineUniData,UniVerse
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