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

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

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonQdrant  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 high-performance vector database with neural network or semantic-based matching
Primary database modelDocument storeSearch engineSearch engineVector DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score134.78
Rank#7  Overall
#1  Search engines
Score5.71
Rank#64  Overall
#8  Search engines
Score1.23
Rank#171  Overall
#6  Vector DBMS
Websiteaws.amazon.com/­documentdbwww.elastic.co/­elasticsearchazure.microsoft.com/­en-us/­services/­searchgithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationaws.amazon.com/­documentdb/­resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmllearn.microsoft.com/­en-us/­azure/­searchqdrant.tech/­documentation
DeveloperElasticMicrosoftQdrant
Initial release2019201020152021
Current release8.6, January 2023V1
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicensecommercialOpen Source infoApache Version 2.0
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 languageJavaRust
Server operating systemshostedAll OS with a Java VMhostedDocker
Linux
macOS
Windows
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-free
Typing infopredefined data types such as float or dateyesyesyesNumbers, Strings, Geo, Boolean
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 indexedyesyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLnoSQL-like query languagenono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP/JSON API
RESTful HTTP APIgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
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
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnoyesno
Triggersnoyes infoby using the 'percolation' featureno
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 serviceCollection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)ES-Hadoop Connectornono
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, tunable consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnono
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 authenticationKey-based authentication

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More resources
Amazon DocumentDBElasticsearchMicrosoft Azure AI SearchQdrant
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Recent citations in the news

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

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