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DBMS > Amazon DocumentDB vs. CouchDB vs. Manticore Search vs. ObjectBox

System Properties Comparison Amazon DocumentDB vs. CouchDB vs. Manticore Search vs. ObjectBox

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonManticore Search  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Multi-storage database for search, including full-text search.Extremely fast embedded database for small devices, IoT and Mobile
Primary database modelDocument storeDocument storeSearch engineObject oriented DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extensionTime Series DBMS infousing the Manticore Columnar LibraryTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score8.30
Rank#47  Overall
#7  Document stores
Score0.29
Rank#302  Overall
#21  Search engines
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Websiteaws.amazon.com/­documentdbcouchdb.apache.orgmanticoresearch.comobjectbox.io
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.couchdb.org/­en/­stablemanual.manticoresearch.comdocs.objectbox.io
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerManticore SoftwareObjectBox Limited
Initial release2019200520172017
Current release3.3.3, December 20236.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoGPL version 2Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++C and C++
Server operating systemshostedAndroid
BSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
macOS
Windows
Android
iOS
Linux
macOS
Windows
Data schemeschema-freeschema-freeFixed schemayes
Typing infopredefined data types such as float or dateyesnoInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.nonoCan index from XMLno
Secondary indexesyesyes infovia viewsyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoSQL-like query languageno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP/JSON APIBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Proprietary native API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Server-side scripts infoStored proceduresnoView functions in JavaScriptuser defined functionsno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoimproved architecture with release 2.0Sharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication
Source-replica replication
Synchronous replication based on Galera libraryonline/offline synchronization between client and server
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsno infoatomic operations within a single document possibleyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
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 rolesAccess rights for users can be defined per databasenoyes
More information provided by the system vendor
Amazon DocumentDBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Manticore SearchObjectBox
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Amazon DocumentDBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Manticore SearchObjectBox
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