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DBMS > Amazon SimpleDB vs. AnzoGraph DB vs. Apache IoTDB vs. IRONdb vs. RDF4J

System Properties Comparison Amazon SimpleDB vs. AnzoGraph DB vs. Apache IoTDB vs. IRONdb vs. RDF4J

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  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 ScioreScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAn 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.
Primary database modelKey-value storeGraph DBMS
RDF store
Time Series DBMSTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteaws.amazon.com/­simpledbcambridgesemantics.com/­anzographiotdb.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.org
Technical documentationdocs.aws.amazon.com/­simpledbdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentation
DeveloperAmazonCambridge SemanticsApache Software FoundationCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20072018201820172004
Current release2.3, January 20211.1.0, April 2023V0.10.20, January 2018
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
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++Java
Server operating systemshostedLinuxAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Unix
Windows
Data schemeschema-freeSchema-free and OWL/RDFS-schema supportyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or datenoyesyes infotext, numeric, histogramsyes
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 automaticallynoyesnoyes
SQL infoSupport of SQLnoSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsRESTful HTTP APIApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
Native API
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C++
Java
Python
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
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyesyes, in Luayes
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationAutomatic shardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication in MPP-Clusterselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency in MPP-ClusterEventual Consistency
Strong Consistency with Raft
Immediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynono infonot needed in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and rolesyesnono

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More resources
Amazon SimpleDBAnzoGraph DBApache IoTDBIRONdbRDF4J infoformerly known as Sesame
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