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DBMS > Apache IoTDB vs. Apache Phoenix vs. Postgres-XL vs. Spark SQL vs. Transbase

System Properties Comparison Apache IoTDB vs. Apache Phoenix vs. Postgres-XL vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  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 scale-out RDBMS with evolutionary schema built on Apache HBaseBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelTime Series DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#183  Overall
#15  Time Series DBMS
Score2.10
Rank#131  Overall
#63  Relational DBMS
Score0.56
Rank#253  Overall
#115  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.20
Rank#327  Overall
#144  Relational DBMS
Websiteiotdb.apache.orgphoenix.apache.orgwww.postgres-xl.orgspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlphoenix.apache.orgwww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationApache Software FoundationApache Software FoundationTransaction Software GmbH
Initial release201820142014 infosince 2012, originally named StormDB20141987
Current release1.1.0, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 201910 R1, October 20183.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoMozilla public licenseOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaCScalaC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
Linux
macOS
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 infoXML type, but no XML query functionalitynono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageyesyes infodistributed, parallel query executionSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
Native API
JDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesuser defined functionsuser defined functionsnoyes
Triggersyesnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioningyes, utilizing Spark Core
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
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkHadoop integrationnono
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 integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoMVCCnoyes
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.yesyesnonono
User concepts infoAccess controlyesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Apache IoTDBApache PhoenixPostgres-XLSpark SQLTransbase
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