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

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

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGreenplum  Xexclude from comparisonIRONdb  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 FlinkAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A 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 MongoDB
Primary database modelTime Series DBMSRelational DBMSTime Series 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
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.08
Rank#367  Overall
#56  Key-value stores
Websiteiotdb.apache.orggreenplum.orgwww.circonus.com/solutions/time-series-database/rdf4j.orggithub.com/­bytedance/­terarkdb
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.greenplum.orgdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software FoundationPivotal Software Inc.Circonus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.ByteDance, originally Terark
Initial release20182005201720042016
Current release1.1.0, April 20237.0.0, September 2023V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen 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++JavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinuxLinux
OS X
Unix
Windows
Data schemeyesyesschema-freeyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyesno
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.noyes infosince Version 4.2nono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like query languageyesSQL-like query language (Circonus Analytics Query Language: CAQL)nono
APIs and other access methodsJDBC
Native API
JDBC
ODBC
HTTP APIJava 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
C
Java
Perl
Python
R
.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
Server-side scripts infoStored proceduresyesyesyes, in Luayesno
Triggersyesyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingAutomatic, metric affinity per nodenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationconfigurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID 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.yesnonoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnonono

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More resources
Apache IoTDBGreenplumIRONdbRDF4J infoformerly known as SesameTerarkDB
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