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DBMS > Apache IoTDB vs. Brytlyt vs. Hypertable vs. InterSystems IRIS vs. Kinetica

System Properties Comparison Apache IoTDB vs. Brytlyt vs. Hypertable vs. InterSystems IRIS vs. Kinetica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBrytlyt  Xexclude from comparisonHypertable  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonKinetica  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed 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 FlinkScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLAn open source BigTable implementation based on distributed file systems such as HadoopA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityFully vectorized database across both GPUs and CPUs
Primary database modelTime Series DBMSRelational DBMSWide column storeDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational 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
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score3.54
Rank#84  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websiteiotdb.apache.orgbrytlyt.iowww.intersystems.com/­products/­intersystems-iriswww.kinetica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.brytlyt.iodocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdocs.kinetica.com
DeveloperApache Software FoundationBrytlytHypertable Inc.InterSystemsKinetica
Initial release20182016200920182012
Current release1.1.0, April 20235.0, August 20230.9.8.11, March 20162023.3, June 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGNU version 3. Commercial license availablecommercialcommercial
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.
Implementation languageJavaC, C++ and CUDAC++C, C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
AIX
Linux
macOS
Ubuntu
Windows
Linux
Data schemeyesyesschema-freedepending on used data modelyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.noyes infospecific XML-type available, but no XML query functionality.yesno
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLSQL-like query languageyesnoyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
C++ API
Thrift
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C++
Java
Perl
PHP
Python
Ruby
.Net
C++
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functions infoin PL/pgSQLnoyesuser defined functions
Triggersyesyesnoyesyes 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)ShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationselectable replication factor on file system levelSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
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.yesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnoyesAccess rights for users and roles on table level
More information provided by the system vendor
Apache IoTDBBrytlytHypertableInterSystems IRISKinetica
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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Apache IoTDBBrytlytHypertableInterSystems IRISKinetica
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