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DBMS > Amazon DocumentDB vs. Elasticsearch vs. Fauna vs. GridDB vs. Microsoft Azure AI Search

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

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure AI Search  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 metricFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Scalable in-memory time series database optimized for IoT and Big DataSearch-as-a-service for web and mobile app development
Primary database modelDocument storeSearch engineDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Time Series DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Key-value store
Relational DBMS
Vector 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
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websiteaws.amazon.com/­documentdbwww.elastic.co/­elasticsearchfauna.comgriddb.netazure.microsoft.com/­en-us/­services/­search
Technical documentationaws.amazon.com/­documentdb/­resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.fauna.comdocs.griddb.netlearn.microsoft.com/­en-us/­azure/­search
DeveloperElasticFauna, Inc.Toshiba CorporationMicrosoft
Initial release20192010201420132015
Current release8.6, January 20235.1, August 2022V1
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicensecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaC++
Server operating systemshostedAll OS with a Java VMhostedLinuxhosted
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nonononono
Secondary indexesyesyes infoAll search fields are automatically indexedyesyesyes
SQL infoSupport of SQLnoSQL-like query languagenoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnoyesuser defined functionsnono
Triggersnoyes infoby using the 'percolation' featurenoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoconsistent hashingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesMulti-source replicationSource-replica replicationyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)ES-Hadoop ConnectornoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
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 ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationnoyesno
User concepts infoAccess controlAccess rights for users and rolesIdentity management, authentication, and access controlAccess rights for users can be defined per databaseyes infousing Azure authentication
More information provided by the system vendor
Amazon DocumentDBElasticsearchFauna infopreviously named FaunaDBGridDBMicrosoft Azure AI Search
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Amazon DocumentDBElasticsearchFauna infopreviously named FaunaDBGridDBMicrosoft Azure AI Search
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