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DBMS > CouchDB vs. FatDB vs. Google Cloud Datastore vs. Microsoft Access

System Properties Comparison CouchDB vs. FatDB vs. Google Cloud Datastore vs. Microsoft Access

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Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)
Primary database modelDocument storeDocument store
Key-value store
Document storeRelational DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.30
Rank#47  Overall
#7  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Websitecouchdb.apache.orgcloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerFatCloudGoogleMicrosoft
Initial release2005201220081992
Current release3.3.3, December 20231902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercialcommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC#C++
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
WindowshostedWindows infoNot a real database server, but making use of DLLs
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyes, details hereyes
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.nono
Secondary indexesyes infovia viewsyesyesyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like query language (GQL)yes infobut not compliant to any SQL standard
APIs and other access methodsRESTful HTTP/JSON API.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresView functions in JavaScriptyes infovia applicationsusing Google App Engineyes infosince Access 2010 using the ACE-engine
Triggersyesyes infovia applicationsCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0ShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate 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.
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possiblenoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction logging
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 can be defined per databaseno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003

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More resources
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"FatDBGoogle Cloud DatastoreMicrosoft Access
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