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DBMS > Amazon DocumentDB vs. Datomic vs. Elasticsearch

System Properties Comparison Amazon DocumentDB vs. Datomic vs. Elasticsearch

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatomic  Xexclude from comparisonElasticsearch  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA 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 storeRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Websiteaws.amazon.com/­documentdbwww.datomic.comwww.elastic.co/­elasticsearch
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.datomic.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.html
DeveloperCognitectElastic
Initial release201920122010
Current release1.0.6735, June 20238.6, January 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoElastic License
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJava
Server operating systemshostedAll OS with a Java VMAll OS with a Java VM
Data schemeschema-freeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistent
Typing infopredefined data types such as float or dateyesyesyes
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 infoAll search fields are automatically indexed
SQL infoSupport of SQLnonoSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
Java
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyes
TriggersnoBy using transaction functionsyes infoby using the 'percolation' feature
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnone infoBut extensive use of caching in the application peersyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noES-Hadoop Connector
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 possiblenono
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 persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentMemcached and Redis integration
User concepts infoAccess controlAccess rights for users and rolesno

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More resources
Amazon DocumentDBDatomicElasticsearch
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Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
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