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

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

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  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.Search-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeSearch engineDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Search engineSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector 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
Score5.59
Rank#63  Overall
#7  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.elastic.co/­elasticsearchfauna.comazure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.fauna.comlearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperElasticFauna, Inc.MicrosoftSphinx Technologies Inc.
Initial release20192010201420152001
Current release8.6, January 2023V13.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicensecommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
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 VMhostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesno
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.nononono
Secondary indexesyesyes infoAll search fields are automatically indexedyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languagenonoSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP/JSON API
RESTful HTTP APIRESTful HTTP APIProprietary protocol
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#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesuser defined functionsnono
Triggersnoyes infoby using the 'percolation' featurenonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning infoconsistent hashingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesMulti-source replicationyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)ES-Hadoop Connectornonono
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
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 operationsnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.Memcached and Redis integrationnono
User concepts infoAccess controlAccess rights for users and rolesIdentity management, authentication, and access controlyes infousing Azure authenticationno

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More resources
Amazon DocumentDBElasticsearchFauna infopreviously named FaunaDBMicrosoft Azure AI SearchSphinx
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