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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Kylin  Xexclude from comparisonHazelcast  Xexclude from comparisonHBase  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 distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackA widely adopted in-memory data gridWide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelTime Series DBMSRelational DBMSKey-value storeWide column 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
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Websiteiotdb.apache.orgkylin.apache.orghazelcast.comhbase.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlkylin.apache.org/­docshazelcast.org/­imdg/­docshbase.apache.org/­book.html
DeveloperApache Software FoundationApache Software Foundation, originally contributed from eBay IncHazelcastApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2018201520082008
Current release1.1.0, April 20233.1.0, July 20205.3.6, November 20232.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAll OS with a Java VMLinux
Unix
Windows infousing Cygwin
Data schemeyesyesschema-freeschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyesyesoptions to bring your own types, AVRO
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.nonoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageANSI SQL for queries (using Apache Calcite)SQL-like query languageno
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
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
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesyes infoCoprocessors in Java
Triggersyesyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
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
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynonono
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)
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.yesnoyesyes
User concepts infoAccess controlyesRole-based access controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources
Apache IoTDBApache KylinHazelcastHBase
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