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DBMS > Apache IoTDB vs. Drizzle vs. Heroic vs. Hypertable vs. Kinetica

System Properties Comparison Apache IoTDB vs. Drizzle vs. Heroic vs. Hypertable vs. Kinetica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDrizzle  Xexclude from comparisonHeroic  Xexclude from comparisonHypertable  Xexclude from comparisonKinetica  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.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 FlinkMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchAn open source BigTable implementation based on distributed file systems such as HadoopFully vectorized database across both GPUs and CPUs
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSWide column storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.13
Rank#335  Overall
#29  Time Series DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Websiteiotdb.apache.orggithub.com/­spotify/­heroicwww.kinetica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlspotify.github.io/­heroicdocs.kinetica.com
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerSpotifyHypertable Inc.Kinetica
Initial release20182008201420092012
Current release1.1.0, April 20237.2.4, September 20120.9.8.11, March 20167.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLOpen Source infoApache 2.0Open Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaC++C, C++
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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
Secondary indexesyesyesyes infovia Elasticsearchrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLSQL-like query languageyes infowith proprietary extensionsnonoSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
JDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
C++ API
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Java
PHP
C++
Java
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnononouser defined functions
Triggersyesno infohooks for callbacks inside the server can be used.nonoyes 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)ShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
yesselectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonono
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.yesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlyesPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess rights for users and roles on table level

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More resources
Apache IoTDBDrizzleHeroicHypertableKinetica
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