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DBMS > Apache Phoenix vs. Databend vs. Greenplum vs. PostgreSQL

System Properties Comparison Apache Phoenix vs. Databend vs. Greenplum vs. PostgreSQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabend  Xexclude from comparisonGreenplum  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Widely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store
Spatial DBMS
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score0.28
Rank#287  Overall
#131  Relational DBMS
Score7.71
Rank#46  Overall
#29  Relational DBMS
Score644.36
Rank#4  Overall
#4  Relational DBMS
Websitephoenix.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
greenplum.orgwww.postgresql.org
Technical documentationphoenix.apache.orgdocs.databend.comdocs.greenplum.orgwww.postgresql.org/­docs
DeveloperApache Software FoundationDatabend LabsPivotal Software Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2014202120051989 info1989: Postgres, 1996: PostgreSQL
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0.59, April 20237.0.0, September 202316.4, August 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoBSD
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
PostgreSQL Flex @ STACKIT offers managed PostgreSQL Instances with adjustable CPU, RAM, storage amount and speed and several extensions available, in enterprise grade to perfectly match all application requirements. All 100% GDPR-compliant.
Implementation languageJavaRustC
Server operating systemsLinux
Unix
Windows
hosted
Linux
macOS
LinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 infosince Version 4.2yes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesyesyesyes infostandard with numerous extensions
APIs and other access methodsJDBCCLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
C
Java
Perl
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsnoyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDACID
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyUsers with fine-grained authorization concept, user rolesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache PhoenixDatabendGreenplumPostgreSQL
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Conferences, events and webinars

PASS Data Community Summit
Seattle, Washington, 4-8 November 2024

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