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DBMS > Amazon CloudSearch vs. Datomic vs. MongoDB

System Properties Comparison Amazon CloudSearch vs. Datomic vs. MongoDB

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonDatomic  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelSearch engineRelational DBMSDocument store
Secondary database modelsSearch engine infointegrated Lucene index, currently in MongoDB Atlas only.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.67
Rank#102  Overall
#9  Search engines
Score2.21
Rank#114  Overall
#54  Relational DBMS
Score443.48
Rank#5  Overall
#1  Document stores
Websiteaws.amazon.com/­cloudsearchwww.datomic.comwww.mongodb.com
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.datomic.comdocs.mongodb.com/­manual
DeveloperAmazonCognitectMongoDB, Inc
Initial release201220122009
Current release0.9.5951, July 20194.2.8, June 2020
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.
Cloud-based only infoOnly available as a cloud serviceyesnono infoMongoDB available as DBaaS (MongoDB Atlas)
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • ScaleGrid for MongoDB: Fully managed hosting for MongoDB database on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.
  • MongoDB Atlas: Deploy a fully managed cloud database on-demand and ready for use in minutes. Available on AWS, Azure, and GCP.
Implementation languageJava, ClojureC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeyesyesschema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.
Typing infopredefined data types such as float or dateyesyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatial
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.no
Secondary indexesyes infoall search fields are automatically indexedyesyes
SQL infoSupport of SQLnonoRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsHTTP APIRESTful HTTP APIproprietary protocol using JSON
Supported programming languagesClojure
Java
Actionscript infoinofficial driver
C
C#
C++
Clojure infoinofficial driver
ColdFusion infoinofficial driver
D infoinofficial driver
Dart infoinofficial driver
Delphi infoinofficial driver
Erlang
Go
Groovy infoinofficial driver
Haskell
Java
JavaScript
Lisp infoinofficial driver
Lua infoinofficial driver
MatLab infoinofficial driver
Perl
PHP
PowerShell infoinofficial driver
Prolog infoinofficial driver
Python
R infoinofficial driver
Ruby
Scala
Smalltalk infoinofficial driver
Server-side scripts infoStored proceduresnoyes infoTransaction FunctionsJavaScript
TriggersnoBy using transaction functionsyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requirednone infoBut extensive use of caching in the application peersSharding infopartitioned by hashed, ranged, or zoned sharding keys
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSnone infoBut extensive use of caching in the application peersMaster-slave replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynonono infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDMulti-document ACID Transactions with snapshot isolation
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 infooptional
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 developmentyes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlauthentication via encrypted signaturesnoAccess rights for users and roles
More information provided by the system vendor
Amazon CloudSearchDatomicMongoDB
Specific characteristicsMongoDB is the leading modern, general purpose data platform, designed to unleash...
» more
Competitive advantagesThe MongoDB Data Platform can be used by developers building OLTP and analytical...
» more
Typical application scenariosInternet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metrics70 million downloads (growing at more than 30 thousand downloads per day). 15,000+...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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More resources
Amazon CloudSearchDatomicMongoDB
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