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DBMS > Amazon SimpleDB vs. CouchDB vs. FatDB vs. Splice Machine

System Properties Comparison Amazon SimpleDB vs. CouchDB vs. FatDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonFatDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeDocument storeDocument store
Key-value store
Relational 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
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­simpledbcouchdb.apache.orgsplicemachine.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.couchdb.org/­en/­stablesplicemachine.com/­how-it-works
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerFatCloudSplice Machine
Initial release2007200520122014
Current release3.3.3, December 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC#Java
Server operating systemshostedAndroid
BSD
Linux
OS X
Solaris
Windows
WindowsLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenonoyesyes
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.no
Secondary indexesyes infoAll columns are indexed automaticallyyes infovia viewsyesyes
SQL infoSupport of SQLnonono infoVia inetgration in SQL Serveryes
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON API.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
Native Spark Datasource
ODBC
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
C#C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoView functions in JavaScriptyes infovia applicationsyes infoJava
Triggersnoyesyes infovia applicationsyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationSharding infoimproved architecture with release 2.0ShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
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 possiblenoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyes, multi-version concurrency control (MVCC)
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.noyes
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 databaseno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon SimpleDBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"FatDBSplice Machine
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