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

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

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Phoenix  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA 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 modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score0.52
Rank#256  Overall
#117  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitedruid.apache.orgphoenix.apache.orgwww.postgres-xl.orgspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdruid.apache.org/­docs/­latest/­designphoenix.apache.orgwww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software Foundation and contributorsApache Software FoundationApache Software FoundationTransaction Software GmbH
Initial release201220142014 infosince 2012, originally named StormDB20141987
Current release29.0.1, April 20245.0-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 license v2Open 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

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Implementation languageJavaJavaCScalaC and C++
Server operating systemsLinux
OS X
Unix
Linux
Unix
Windows
Linux
macOS
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyes 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 for queryingyesyes infodistributed, parallel query executionSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
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 proceduresnouser defined functionsuser defined functionsnoyes
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.noyesnonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess 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 DruidApache PhoenixPostgres-XLSpark SQLTransbase
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