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DBMS > Amazon SimpleDB vs. CouchDB vs. IRONdb vs. RDF4J vs. Splice Machine

System Properties Comparison Amazon SimpleDB vs. CouchDB vs. IRONdb vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  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.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeDocument storeTime Series DBMSRDF storeRelational 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
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­simpledbcouchdb.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.orgsplicemachine.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.couchdb.org/­en/­stabledocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20072005201720042014
Current release3.3.3, December 2023V0.10.20, January 20183.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC and C++JavaJava
Server operating systemshostedAndroid
BSD
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or datenonoyes infotext, numeric, histogramsyesyes
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 infoAll columns are indexed automaticallyyes infovia viewsnoyesyes
SQL infoSupport of SQLnonoSQL-like query language (Circonus Analytics Query Language: CAQL)noyes
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON APIHTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
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
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoView functions in JavaScriptyes, in Luayesyes infoJava
Triggersnoyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationSharding infoimproved architecture with release 2.0Automatic, metric affinity per nodenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
configurable replication factor, datacenter awarenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate 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 infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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 databasenonoAccess 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"IRONdbRDF4J infoformerly known as SesameSplice Machine
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