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DBMS > Apache IoTDB vs. EXASOL vs. Ingres vs. IRONdb vs. Kinetica

System Properties Comparison Apache IoTDB vs. EXASOL vs. Ingres vs. IRONdb vs. Kinetica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEXASOL  Xexclude from comparisonIngres  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  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 FlinkHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Well established RDBMSA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUs
Primary database modelTime Series DBMSRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websiteiotdb.apache.orgwww.exasol.comwww.actian.com/­databases/­ingreswww.circonus.com/solutions/time-series-database/www.kinetica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.exasol.com/­resourcesdocs.actian.com/­ingresdocs.circonus.com/irondb/category/getting-starteddocs.kinetica.com
DeveloperApache Software FoundationExasolActian CorporationCirconus LLC.Kinetica
Initial release201820001974 infooriginally developed at University Berkely in early 1970s20172012
Current release1.1.0, April 202311.2, May 2022V0.10.20, January 20187.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC and C++C, C++
Server operating systemsAll OS with a Java VM (>= 1.8)AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
LinuxLinux
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infotext, numeric, histogramsyes
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 infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageyesyesSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
.Net
JDBC
ODBC
WebSocket
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
HTTP APIJDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
Lua
Python
R
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functionsyesyes, in Luauser defined functions
Triggersyesyesyesnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyAutomatic, metric affinity per nodeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasIngres Replicatorconfigurable replication factor, datacenter awareSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infoHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
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.yesyesnonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlyesAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardnoAccess rights for users and roles on table level

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More resources
Apache IoTDBEXASOLIngresIRONdbKinetica
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