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DBMS > Apache IoTDB vs. IRONdb vs. RRDtool vs. STSdb vs. ToroDB

System Properties Comparison Apache IoTDB vs. IRONdb vs. RRDtool vs. STSdb vs. ToroDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIRONdb  Xexclude from comparisonRRDtool  Xexclude from comparisonSTSdb  Xexclude from comparisonToroDB  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.ToroDB 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 simplicityIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Key-Value Store with special method for indexing infooptimized for high performance using a special indexing methodA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelTime Series DBMSTime Series DBMSTime Series DBMSKey-value storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteiotdb.apache.orgwww.circonus.com/solutions/time-series-database/oss.oetiker.ch/­rrdtoolgithub.com/­STSSoft/­STSdb4github.com/­torodb/­server
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.circonus.com/irondb/category/getting-startedoss.oetiker.ch/­rrdtool/­doc
DeveloperApache Software FoundationCirconus LLC.Tobias OetikerSTS Soft SC8Kdata
Initial release20182017199920112016
Current release1.1.0, April 2023V0.10.20, January 20181.8.0, 20224.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL V2 and FLOSSOpen Source infoGPLv2, commercial license availableOpen Source infoAGPL-V3
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++C infoImplementations in Java (e.g. RRD4J) and C# availableC#Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxHP-UX
Linux
WindowsAll OS with a Java 7 VM
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsNumeric data onlyyes infoprimitive types and user defined types (classes)yes infostring, integer, double, boolean, date, object_id
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 infoExporting into and restoring from XML files possibleno
Secondary indexesyesnonono
SQL infoSupport of SQLSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)nono
APIs and other access methodsJDBC
Native API
HTTP APIin-process shared library
Pipes
.NET Client 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 infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
C#
Java
Server-side scripts infoStored proceduresyesyes, in Luanono
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic, metric affinity per nodenonenoneSharding
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 Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate consistency per node, eventual consistency across nodesnoneEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoby using the rrdcached daemonyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
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 for users and roles

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More resources
Apache IoTDBIRONdbRRDtoolSTSdbToroDB
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