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DBMS > Amazon DocumentDB vs. Elasticsearch vs. Microsoft Azure AI Search vs. Solr

System Properties Comparison Amazon DocumentDB vs. Elasticsearch vs. Microsoft Azure AI Search vs. Solr

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA 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 metricSearch-as-a-service for web and mobile app developmentA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeSearch engineSearch engineSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Vector DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score135.35
Rank#7  Overall
#1  Search engines
Score5.59
Rank#63  Overall
#7  Search engines
Score42.91
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­documentdbwww.elastic.co/­elasticsearchazure.microsoft.com/­en-us/­services/­searchsolr.apache.org
Technical documentationaws.amazon.com/­documentdb/­resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmllearn.microsoft.com/­en-us/­azure/­searchsolr.apache.org/­resources.html
DeveloperElasticMicrosoftApache Software Foundation
Initial release2019201020152006
Current release8.6, January 2023V19.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicensecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemshostedAll OS with a Java VMhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes 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 indexesyesyes infoAll search fields are automatically indexedyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query languagenoSolr Parallel SQL Interface
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP/JSON API
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
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 proceduresnoyesnoJava plugins
Triggersnoyes infoby using the 'percolation' featurenoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesyes infoImplicit feature of the cloud serviceyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)ES-Hadoop Connectornospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnonooptimistic 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 integrationnoyes
User concepts infoAccess controlAccess rights for users and rolesyes infousing Azure authenticationyes

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More resources
Amazon DocumentDBElasticsearchMicrosoft Azure AI SearchSolr
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