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DBMS > Elasticsearch vs. Solr vs. Sphinx vs. Sqrrl

System Properties Comparison Elasticsearch vs. Solr vs. Sphinx vs. Sqrrl

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databasesAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelSearch engineSearch engineSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score134.78
Rank#7  Overall
#1  Search engines
Score44.28
Rank#24  Overall
#3  Search engines
Score6.03
Rank#60  Overall
#6  Search engines
Websitewww.elastic.co/­elasticsearchsolr.apache.orgsphinxsearch.comsqrrl.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlsolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperElasticApache Software FoundationSphinx Technologies Inc.Amazon infooriginally Sqrrl Data, Inc.
Initial release2010200620012012
Current release8.6, January 20239.5.0, February 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++Java
Server operating systemsAll 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
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free
Typing infopredefined data types such as float or dateyesyes 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.noyes
Secondary indexesyes infoAll search fields are automatically indexedyes infoAll search fields are automatically indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)no
APIs and other access methodsJava API
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
Proprietary protocolAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.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
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesJava pluginsnono
Triggersyes infoby using the 'percolation' featureyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectorspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.Memcached and Redis integrationyes
User concepts infoAccess controlyesnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
ElasticsearchSolrSphinxSqrrl
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