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DBMS > CouchDB vs. Google Cloud Datastore vs. IRONdb vs. Tkrzw

System Properties Comparison CouchDB vs. Google Cloud Datastore vs. IRONdb vs. Tkrzw

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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 comparisonIRONdb  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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 PlatformA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument storeDocument storeTime Series DBMSKey-value store
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.26
Rank#45  Overall
#7  Document stores
Score4.49
Rank#79  Overall
#12  Document stores
Score0.09
Rank#354  Overall
#51  Key-value stores
Websitecouchdb.apache.orgcloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/dbmx.net/­tkrzw
Technical documentationdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogleCirconus LLC.Mikio Hirabayashi
Initial release2005200820172020
Current release3.3.3, December 2023V0.10.20, January 20180.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC and C++C++
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedLinuxLinux
macOS
Data schemeschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenoyes, details hereyes infotext, numeric, histogramsno
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.nononono
Secondary indexesyes infovia viewsyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsRESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP 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
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresView functions in JavaScriptusing Google App Engineyes, in Luano
TriggersyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0ShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownono
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.Immediate consistency per node, eventual consistency across nodesImmediate 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 Transactionsno
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes infousing specific database classes
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)nono

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More resources
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud DatastoreIRONdbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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