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DBMS > Amazon SimpleDB vs. CouchDB vs. IRONdb vs. RDF4J vs. Spark SQL

System Properties Comparison Amazon SimpleDB vs. CouchDB vs. IRONdb vs. RDF4J vs. Spark SQL

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 comparisonSpark SQL  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.Spark SQL is a component on top of 'Spark Core' for structured data processing
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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­simpledbcouchdb.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.orgspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­simpledbdocs.couchdb.org/­en/­stabledocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
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.Apache Software Foundation
Initial release20072005201720042014
Current release3.3.3, December 2023V0.10.20, January 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0
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++JavaScala
Server operating systemshostedAndroid
BSD
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Unix
Windows
Linux
OS X
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.nonono
Secondary indexesyes infoAll columns are indexed automaticallyyes infovia viewsnoyesno
SQL infoSupport of SQLnonoSQL-like query language (Circonus Analytics Query Language: CAQL)noSQL-like DML and DDL statements
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
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoView functions in JavaScriptyes, in Luayesno
Triggersnoyesnoyesno
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 nodenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
configurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
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 nodes
Foreign keys infoReferential integritynononono
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 usedno
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyesyes
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.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 databasenonono

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More resources
Amazon SimpleDBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"IRONdbRDF4J infoformerly known as SesameSpark SQL
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