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

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

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFauna 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 development
Primary database modelDocument storeDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Search engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
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
Websiteaws.amazon.com/­documentdbfauna.comazure.microsoft.com/­en-us/­services/­search
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.fauna.comlearn.microsoft.com/­en-us/­azure/­search
DeveloperFauna, Inc.Microsoft
Initial release201920142015
Current releaseV1
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScala
Server operating systemshostedhostedhosted
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLnonono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIRESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnouser defined functionsno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoconsistent hashingSharding 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 replicasMulti-source 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)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users and rolesIdentity management, authentication, and access controlyes infousing Azure authentication

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More resources
Amazon DocumentDBFauna infopreviously named FaunaDBMicrosoft Azure AI Search
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Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
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