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DBMS > Amazon SimpleDB vs. Apache IoTDB vs. IRONdb vs. RDF4J vs. TerarkDB

System Properties Comparison Amazon SimpleDB vs. Apache IoTDB vs. IRONdb vs. RDF4J vs. TerarkDB

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTerarkDB  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 ScioreAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA 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.A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelKey-value storeTime Series DBMSTime Series DBMSRDF storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.08
Rank#367  Overall
#56  Key-value stores
Websiteaws.amazon.com/­simpledbiotdb.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.orggithub.com/­bytedance/­terarkdb
Technical documentationdocs.aws.amazon.com/­simpledbiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperAmazonApache Software FoundationCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.ByteDance, originally Terark
Initial release20072018201720042016
Current release1.1.0, April 2023V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++JavaC++
Server operating systemshostedAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Unix
Windows
Data schemeschema-freeyesschema-freeyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or datenoyesyes infotext, numeric, histogramsyesno
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 automaticallyyesnoyesno
SQL infoSupport of SQLnoSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)nono
APIs and other access methodsRESTful HTTP APIJDBC
Native API
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
C++ API
Java API
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
.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++
Java
Server-side scripts infoStored proceduresnoyesyes, in Luayesno
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationhorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic, metric affinity per nodenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasconfigurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Strong Consistency with Raft
Immediate 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 applicationnonoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesnonono

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More resources
Amazon SimpleDBApache IoTDBIRONdbRDF4J infoformerly known as SesameTerarkDB
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