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DBMS > Elasticsearch vs. Kinetica vs. Microsoft Azure AI Search vs. Solr

System Properties Comparison Elasticsearch vs. Kinetica vs. Microsoft Azure AI Search vs. Solr

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSolr  Xexclude from comparison
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 metricFully vectorized database across both GPUs and CPUsSearch-as-a-service for web and mobile app developmentA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelSearch engineRelational DBMSSearch engineSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
Time Series DBMS
Vector DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.elastic.co/­elasticsearchwww.kinetica.comazure.microsoft.com/­en-us/­services/­searchsolr.apache.org
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.kinetica.comlearn.microsoft.com/­en-us/­azure/­searchsolr.apache.org/­resources.html
DeveloperElasticKineticaMicrosoftApache Software Foundation
Initial release2010201220152006
Current release8.6, January 20237.1, August 2021V19.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++Java
Server operating systemsAll OS with a Java VMLinuxhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesyes infoAll search fields are automatically indexedyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnoSolr Parallel SQL Interface
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesuser defined functionsnoJava plugins
Triggersyes infoby using the 'percolation' featureyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoImplicit feature of the cloud serviceyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectornonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
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, allImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelyes infousing Azure authenticationyes

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More resources
ElasticsearchKineticaMicrosoft Azure AI SearchSolr
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