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DBMS > Amazon DocumentDB vs. Elasticsearch

System Properties Comparison Amazon DocumentDB vs. Elasticsearch

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Our visitors often compare Amazon DocumentDB and Elasticsearch with MongoDB, PostgreSQL and OpenSearch.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonElasticsearch  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 metric
Primary database modelDocument storeSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.79
Rank#157  Overall
#29  Document stores
Score135.74
Rank#7  Overall
#1  Search engines
Websiteaws.amazon.com/­documentdbwww.elastic.co/­elasticsearch
Technical documentationaws.amazon.com/­documentdb/­resourceswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.html
DeveloperElastic
Initial release20192010
Current release8.6, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic License
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedAll OS with a Java VM
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistent
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java 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
Server-side scripts infoStored proceduresnoyes
Triggersnoyes infoby using the 'percolation' feature
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)ES-Hadoop Connector
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, all
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integration
User concepts infoAccess controlAccess rights for users and roles

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More resources
Amazon DocumentDBElasticsearch
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