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DBMS > Apache IoTDB vs. MonetDB vs. MySQL vs. Spark SQL vs. Trafodion

System Properties Comparison Apache IoTDB vs. MonetDB vs. MySQL vs. Spark SQL vs. Trafodion

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMonetDB  Xexclude from comparisonMySQL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. 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 relational database management system that stores data in columnsWidely used open source RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infoKey/Value like access via memcached APIRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#183  Overall
#15  Time Series DBMS
Score1.78
Rank#149  Overall
#69  Relational DBMS
Score1101.50
Rank#2  Overall
#2  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websiteiotdb.apache.orgwww.monetdb.orgwww.mysql.comspark.apache.org/­sqltrafodion.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.monetdb.org/­Documentationdev.mysql.com/­docspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperApache Software FoundationMonetDB BVOracle infosince 2010, originally MySQL AB, then SunApache Software FoundationApache Software Foundation, originally developed by HP
Initial release20182004199520142014
Current release1.1.0, April 2023Dec2023 (11.49), December 20238.3.0, January 20243.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMozilla Public License 2.0Open Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageJavaCC and C++ScalaC++, Java
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageyes infoSQL 2003 with some extensionsyes infowith proprietary extensionsSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
Native API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyesyes, in SQL, C, Ryes infoproprietary syntaxnoJava Stored Procedures
Triggersyesyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding via remote tableshorizontal partitioning, sharding with MySQL Cluster or MySQL Fabricyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone infoSource-replica replication available in experimental statusMulti-source replication
Source-replica replication
noneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infonot for MyISAM storage enginenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infonot for MyISAM storage enginenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyesyes
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.yesyesnono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or rolesnofine grained access rights according to SQL-standard

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More resources
Apache IoTDBMonetDBMySQLSpark SQLTrafodion
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