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DBMS > Apache IoTDB vs. IRONdb vs. RDF4J vs. TerarkDB vs. UniData,UniVerse

System Properties Comparison Apache IoTDB vs. IRONdb vs. RDF4J vs. TerarkDB vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTerarkDB  Xexclude from comparisonUniData,UniVerse  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 key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelTime Series DBMSTime Series DBMSRDF storeKey-value storeMultivalue DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score2.85
Rank#98  Overall
#1  Multivalue DBMS
Websiteiotdb.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.orggithub.com/­bytedance/­terarkdbwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperApache Software FoundationCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.ByteDance, originally TerarkRocket Software
Initial release20182017200420161985
Current release1.1.0, April 2023V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial inforestricted open source version availablecommercial
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++JavaC++C
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Unix
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyes infoRDF Schemasschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesnooptional
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 indexesyesnoyesnoyes
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
C++ API
Java API
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based 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
Java
PHP
Python
C++
Java
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresyesyes, in Luayesnoyes
Triggersyesnoyesnoyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic, metric affinity per nodenonenonenone
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 awarenonenoneSource-replica replication
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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoIsolation support depends on the API usednoACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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
User concepts infoAccess controlyesnononoAccess rights according to SQL-standard and operating system based

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More resources
Apache IoTDBIRONdbRDF4J infoformerly known as SesameTerarkDBUniData,UniVerse
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