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DBMS > Amazon SimpleDB vs. CouchDB vs. Google Cloud Datastore vs. IRONdb

System Properties Comparison Amazon SimpleDB vs. CouchDB vs. Google Cloud Datastore vs. IRONdb

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreA 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 simplicity
Primary database modelKey-value storeDocument storeDocument storeTime Series DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score9.30
Rank#45  Overall
#7  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Websiteaws.amazon.com/­simpledbcouchdb.apache.orgcloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/
Technical documentationdocs.aws.amazon.com/­simpledbdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogleCirconus LLC.
Initial release2007200520082017
Current release3.3.3, December 2023V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC and C++
Server operating systemshostedAndroid
BSD
Linux
OS X
Solaris
Windows
hostedLinux
Data schemeschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenonoyes, details hereyes infotext, numeric, histograms
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.nonono
Secondary indexesyes infoAll columns are indexed automaticallyyes infovia viewsyesno
SQL infoSupport of SQLnonoSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
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
Server-side scripts infoStored proceduresnoView functions in JavaScriptusing Google App Engineyes, in Lua
TriggersnoyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationSharding infoimproved architecture with release 2.0ShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replication using Paxosconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual 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 nodes
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationno infoatomic operations within a single document possibleACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyes
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.nonono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users can be defined per databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Amazon SimpleDBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud DatastoreIRONdb
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