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DBMS > Apache IoTDB vs. HBase vs. Riak TS vs. TDengine

System Properties Comparison Apache IoTDB vs. HBase vs. Riak TS vs. TDengine

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHBase  Xexclude from comparisonRiak TS  Xexclude from comparisonTDengine  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 FlinkWide-column store based on Apache Hadoop and on concepts of BigTableRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVTime Series DBMS and big data platform
Primary database modelTime Series DBMSWide column storeTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteiotdb.apache.orghbase.apache.orggithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhbase.apache.org/­book.htmlwww.tiot.jp/­riak-docs/­riak/­ts/­latestdocs.tdengine.com
DeveloperApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by PowersetOpen Source, formerly Basho TechnologiesTDEngine, previously Taos Data
Initial release2018200820152019
Current release1.1.0, April 20232.3.4, January 20213.0.0, September 20223.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2Open SourceOpen Source infoGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaErlangC
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows infousing Cygwin
Linux
OS X
Linux
Windows
Data schemeyesschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROnoyes
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 indexesyesnorestrictedno
SQL infoSupport of SQLSQL-like query languagenoyes, limitedStandard SQL with extensions for time-series applications
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP API
Thrift
HTTP API
Native Erlang Interface
JDBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresyesyes infoCoprocessors in JavaErlangno
Triggersyesyesyes infopre-commit hooks and post-commit hooksyes, via alarm monitoring
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 replicasMulti-source replication
Source-replica replication
selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyes
User concepts infoAccess controlyesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoyes
More information provided by the system vendor
Apache IoTDBHBaseRiak TSTDengine
Specific characteristicsTDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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