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DBMS > Amazon Neptune vs. Apache IoTDB vs. Graph Engine vs. IRONdb vs. RDF4J

System Properties Comparison Amazon Neptune vs. Apache IoTDB vs. Graph Engine vs. IRONdb vs. RDF4J

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  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.
DescriptionFast, reliable graph database built for the cloudAn 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 in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA 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 modelGraph DBMS
RDF store
Time Series DBMSGraph DBMS
Key-value store
Time Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteaws.amazon.com/­neptuneiotdb.apache.orgwww.graphengine.iowww.circonus.com/solutions/time-series-database/rdf4j.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentation
DeveloperAmazonApache Software FoundationMicrosoftCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20172018201020172004
Current release1.1.0, April 2023V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoMIT LicensecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava.NET and CC and C++Java
Server operating systemshostedAll OS with a Java VM (>= 1.8).NETLinuxLinux
OS X
Unix
Windows
Data schemeschema-freeyesyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyesyes 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.nononono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoSQL-like query languagenoSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Native API
RESTful HTTP APIHTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
.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 proceduresnoyesyesyes, in Luayes
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.selectable 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 methodsnoIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes 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)yesnono

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More resources
Amazon NeptuneApache IoTDBGraph Engine infoformer name: TrinityIRONdbRDF4J infoformerly known as Sesame
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