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DBMS > Apache IoTDB vs. IRONdb vs. Spark SQL vs. STSdb vs. ToroDB

System Properties Comparison Apache IoTDB vs. IRONdb vs. Spark SQL vs. STSdb vs. ToroDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  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 simplicitySpark SQL is a component on top of 'Spark Core' for structured data processingKey-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 DBMSRelational 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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteiotdb.apache.orgwww.circonus.com/solutions/time-series-database/spark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4github.com/­torodb/­server
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationCirconus LLC.Apache Software FoundationSTS Soft SC8Kdata
Initial release20182017201420112016
Current release1.1.0, April 2023V0.10.20, January 20183.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open 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++ScalaC#Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Windows
WindowsAll OS with a Java 7 VM
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyes 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.nononono
Secondary indexesyesnonono
SQL infoSupport of SQLSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsno
APIs and other access methodsJDBC
Native API
HTTP APIJDBC
ODBC
.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
Java
Python
R
Scala
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 nodeyes, utilizing Spark CorenoneSharding
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 Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate consistency per node, eventual consistency across nodesEventual 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 datayesyesyesyesyes
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.yesnono
User concepts infoAccess controlyesnononoAccess rights for users and roles

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More resources
Apache IoTDBIRONdbSpark SQLSTSdbToroDB
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