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DBMS > Apache IoTDB vs. CrateDB vs. Kinetica vs. mSQL

System Properties Comparison Apache IoTDB vs. CrateDB vs. Kinetica vs. mSQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCrateDB  Xexclude from comparisonKinetica  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparison
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 FlinkDistributed Database based on LuceneFully vectorized database across both GPUs and CPUsmSQL (Mini SQL) is a simple and lightweight RDBMS
Primary database modelTime Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score0.73
Rank#229  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score1.67
Rank#151  Overall
#70  Relational DBMS
Websiteiotdb.apache.orgcratedb.comwww.kinetica.comhughestech.com.au/­products/­msql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcratedb.com/­docsdocs.kinetica.com
DeveloperApache Software FoundationCrateKineticaHughes Technologies
Initial release2018201320121994
Current release1.1.0, April 20237.1, August 20214.4, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Sourcecommercialcommercial infofree licenses can be provided
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaC, C++C
Server operating systemsAll OS with a Java VM (>= 1.8)All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like DML and DDL statementsA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggers
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C++
Java
JavaScript (Node.js)
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
Server-side scripts infoStored proceduresyesuser defined functions (Javascript)user defined functionsno
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingnone
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 on table/partition-levelSource-replica replicationnone
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
Eventual Consistency
Read-after-write consistency on record level
Immediate Consistency or Eventual Consistency depending on configurationnone
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategynono
Concurrency infoSupport for concurrent manipulation of datayesyesyesno
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlyesrights management via user accountsAccess rights for users and roles on table levelno
More information provided by the system vendor
Apache IoTDBCrateDBKineticamSQL infoMini SQL
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
Apache IoTDBCrateDBKineticamSQL infoMini SQL
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