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DBMS > CouchDB vs. Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. PouchDB vs. RDF4J

System Properties Comparison CouchDB vs. Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. PouchDB vs. RDF4J

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 comparisonRDF4J infoformerly known as Sesame  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 CouchDBRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument storeDocument storeRelational DBMS infocolumn orientedDocument storeRDF store
Secondary database modelsSpatial DBMS infousing the Geocouch extensionDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.30
Rank#45  Overall
#7  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecouchdb.apache.orgcloud.google.com/­datastoreazure.microsoft.com/­services/­data-explorerpouchdb.comrdf4j.org
Technical documentationdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerpouchdb.com/­guidesrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogleMicrosoftApache Software FoundationSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20052008201920122004
Current release3.3.3, December 2023cloud service with continuous releases7.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercialOpen SourceOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangJavaScriptJava
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedhostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Unix
Windows
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or datenoyes, details hereyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyes
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 viewsyesall fields are automatically indexedyes infovia viewsyes
SQL infoSupport of SQLnoSQL-like query language (GQL)Kusto Query Language (KQL), SQL subsetnono
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
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
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
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScriptJava
PHP
Python
Server-side scripts infoStored proceduresView functions in JavaScriptusing Google App EngineYes, possible languages: KQL, Python, RView functions in JavaScriptyes
TriggersyesCallbacks using the Google Apps Engineyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
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-loungenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
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 TransactionsnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes infoin-memory storage is supported as well
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 Authenticationnono

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CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud DatastoreMicrosoft Azure Data ExplorerPouchDBRDF4J infoformerly known as Sesame
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