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DBMS > Apache IoTDB vs. IRONdb vs. MonetDB vs. RDF4J vs. TerarkDB

System Properties Comparison Apache IoTDB vs. IRONdb vs. MonetDB vs. RDF4J vs. TerarkDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIRONdb  Xexclude from comparisonMonetDB  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.
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 simplicityA relational database management system that stores data in columnsRDF4J 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 modelTime Series DBMSTime Series DBMSRelational DBMSRDF storeKey-value store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.08
Rank#367  Overall
#56  Key-value stores
Websiteiotdb.apache.orgwww.circonus.com/solutions/time-series-database/www.monetdb.orgrdf4j.orggithub.com/­bytedance/­terarkdb
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.circonus.com/irondb/category/getting-startedwww.monetdb.org/­Documentationrdf4j.org/­documentationbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software FoundationCirconus LLC.MonetDB BVSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.ByteDance, originally Terark
Initial release20182017200420042016
Current release1.1.0, April 2023V0.10.20, January 2018Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMozilla Public License 2.0Open Source infoEclipse Distribution License (EDL), v1.0.commercial inforestricted open source version 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++CJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
Data schemeyesschema-freeyesyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyesno
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 indexesyesnoyesyesno
SQL infoSupport of SQLSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)yes infoSQL 2003 with some extensionsnono
APIs and other access methodsJDBC
Native API
HTTP APIJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
C++ API
Java API
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
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
PHP
Python
C++
Java
Server-side scripts infoStored proceduresyesyes, in Luayes, in SQL, C, Ryesno
Triggersyesnoyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic, metric affinity per nodeSharding via remote tablesnonenone
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 awarenone infoSource-replica replication available in experimental statusnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID 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 controlyesnofine grained access rights according to SQL-standardnono

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More resources
Apache IoTDBIRONdbMonetDBRDF4J infoformerly known as SesameTerarkDB
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