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DBMS > Apache IoTDB vs. HBase vs. Kingbase vs. Postgres-XL

System Properties Comparison Apache IoTDB vs. HBase vs. Kingbase vs. Postgres-XL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHBase  Xexclude from comparisonKingbase  Xexclude from comparisonPostgres-XL  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 BigTableAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelTime Series DBMSWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Spatial 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
Score0.45
Rank#262  Overall
#123  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteiotdb.apache.orghbase.apache.orgwww.kingbase.com.cnwww.postgres-xl.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhbase.apache.org/­book.htmlwww.postgres-xl.org/­documentation
DeveloperApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by PowersetBeiJing KINGBASE Information technologies inc.
Initial release2018200819992014 infosince 2012, originally named StormDB
Current release1.1.0, April 20232.3.4, January 2021V8.0, August 202110 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2commercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and JavaC
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows infousing Cygwin
Linux
Windows
Linux
macOS
Data schemeyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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.nonoyesyes infoXML type, but no XML query functionality
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenoStandard with numerous extensionsyes infodistributed, parallel query execution
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP API
Thrift
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesyes infoCoprocessors in Javauser defined functionsuser defined functions
Triggersyesyesyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioning (by range, list and hash) and vertical partitioninghorizontal partitioning
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
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)ACIDACID infoMVCC
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.yesyesno
User concepts infoAccess controlyesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache IoTDBHBaseKingbasePostgres-XL
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