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DBMS > CouchDB vs. Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. PouchDB

System Properties Comparison CouchDB vs. Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. PouchDB

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Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully managed big data interactive analytics platformJavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument storeDocument storeRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.37
Rank#34  Overall
#5  Document stores
Score4.81
Rank#67  Overall
#12  Document stores
Score2.33
Rank#104  Overall
#50  Relational DBMS
Score2.97
Rank#88  Overall
#16  Document stores
Websitecouchdb.apache.orgcloud.google.com/­datastoreazure.microsoft.com/­services/­data-explorerpouchdb.com
Technical documentationdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerpouchdb.com/­guides
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogleMicrosoftApache Software Foundation
Initial release2005200820192012
Current release2.3.1, March 20197.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangJavaScript
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedhostedserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyes, details hereyesno
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.nonoyesno
Secondary indexesyes infovia viewsyesyes infovia views
SQL infoSupport of SQLnoSQL-like query language (GQL)Kusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScript
Server-side scripts infoStored proceduresView functions in JavaScriptusing Google App EngineYes. Languages: KQL, Python, RView functions in JavaScript
TriggersyesCallbacks using the Google Apps EngineTable-level update policy rules can be used to automatically run a query and ingest its results when data is ingested into another table.yes
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0ShardingSharding infoImplicit feature of the cloud serviceSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replication
Master-slave replication
Multi-Master replication using Paxosyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Master-master replication infoalso with CouchDB databases
Master-slave replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authenticationno

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