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

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

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonDrizzle  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.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 ScioreMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.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 storeRelational DBMSTime Series DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.circonus.com/solutions/time-series-database/rdf4j.orgsplicemachine.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperAmazonDrizzle project, originally started by Brian AkerCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20072008201720042014
Current release7.2.4, September 2012V0.10.20, January 20183.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLcommercialOpen 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 languageC++C and C++JavaJava
Server operating systemshostedFreeBSD
Linux
OS X
LinuxLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or datenoyesyes 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.no
Secondary indexesyes infoAll columns are indexed automaticallyyesnoyesyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like query language (Circonus Analytics Query Language: CAQL)noyes
APIs and other access methodsRESTful HTTP APIJDBCHTTP 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++
Java
PHP
.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 proceduresnonoyes, in Luayesyes infoJava
Triggersnono infohooks for callbacks inside the server can be used.noyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingAutomatic, 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 methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDnoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, 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.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Pluggable authentication mechanisms infoe.g. LDAP, HTTPnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon SimpleDBDrizzleIRONdbRDF4J infoformerly known as SesameSplice Machine
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