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DBMS > Apache IoTDB vs. Hazelcast vs. HBase vs. TerarkDB

System Properties Comparison Apache IoTDB vs. Hazelcast vs. HBase vs. TerarkDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHazelcast  Xexclude from comparisonHBase  Xexclude from comparisonTerarkDB  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 FlinkA widely adopted in-memory data gridWide-column store based on Apache Hadoop and on concepts of BigTableA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelTime Series DBMSKey-value storeWide column storeKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteiotdb.apache.orghazelcast.comhbase.apache.orggithub.com/­bytedance/­terarkdb
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docshbase.apache.org/­book.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software FoundationHazelcastApache Software Foundation infoApache top-level project, originally developed by PowersetByteDance, originally Terark
Initial release2018200820082016
Current release1.1.0, April 20235.3.6, November 20232.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache version 2commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux
Unix
Windows infousing Cygwin
Data schemeyesschema-freeschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROno
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 infothe object must implement a serialization strategynono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like query languageSQL-like query languagenono
APIs and other access methodsJDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
C++ API
Java API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesyes infoCoprocessors in Javano
Triggersyesyes infoEventsyesno
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 replicasyes infoReplicated MapMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitedSingle 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.yesyesyesyes
User concepts infoAccess controlyesRole-based access controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno

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More resources
Apache IoTDBHazelcastHBaseTerarkDB
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