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DBMS > IBM Cloudant vs. Microsoft Azure AI Search vs. Solr vs. Sphinx

System Properties Comparison IBM Cloudant vs. Microsoft Azure AI Search vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameIBM Cloudant  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionDatabase as a Service offering based on Apache CouchDBSearch-as-a-service for web and mobile app developmentA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeSearch engineSearch engineSearch engine
Secondary database modelsVector DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.75
Rank#104  Overall
#19  Document stores
Score5.52
Rank#59  Overall
#6  Search engines
Score41.02
Rank#24  Overall
#3  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.ibm.com/­products/­cloudantazure.microsoft.com/­en-us/­services/­searchsolr.apache.orgsphinxsearch.com
Technical documentationcloud.ibm.com/­docs/­Cloudantlearn.microsoft.com/­en-us/­azure/­searchsolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014MicrosoftApache Software FoundationSphinx Technologies Inc.
Initial release2010201520062001
Current releaseV19.6.1, May 20243.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangJavaC++
Server operating systemshostedhostedAll 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
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or datenoyesyes infosupports customizable data types and automatic typingno
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.nonoyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnonoSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP/JSON APIRESTful HTTP APIJava API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesC#
Java
JavaScript
Objective-C
PHP
Ruby
C#
Java
JavaScript
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
Server-side scripts infoStored proceduresView functions (Map-Reduce) in JavaScriptnoJava pluginsno
Triggersyesnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud serviceyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a document possiblenooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 controlAccess rights for users can be defined per databaseyes infousing Azure authenticationyesno

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More resources
IBM CloudantMicrosoft Azure AI SearchSolrSphinx
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