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DBMS > Apache IoTDB vs. IRONdb vs. RDF4J vs. Realm vs. Splice Machine

System Properties Comparison Apache IoTDB vs. IRONdb vs. RDF4J vs. Realm vs. Splice Machine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRealm  Xexclude from comparisonSplice Machine  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn 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 DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSTime Series DBMSRDF storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score7.60
Rank#52  Overall
#9  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteiotdb.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.orgrealm.iosplicemachine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationrealm.io/­docssplicemachine.com/­how-it-works
DeveloperApache Software FoundationCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Realm, acquired by MongoDB in May 2019Splice Machine
Initial release20182017200420142014
Current release1.1.0, April 2023V0.10.20, January 20183.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open SourceOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++JavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Unix
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyes infoRDF Schemasyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyesyes
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 indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)nonoyes
APIs and other access methodsJDBC
Native API
HTTP 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 languagesC
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
.Net
Java infowith Android only
Objective-C
React Native
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesyes, in Luayesno inforuns within the applications so server-side scripts are unnecessaryyes infoJava
Triggersyesnoyesyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic, metric affinity per nodenonenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasconfigurable replication factor, datacenter awarenonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usedACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoIn-Memory realmyes
User concepts infoAccess controlyesnonoyesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBIRONdbRDF4J infoformerly known as SesameRealmSplice Machine
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