DBMS > Apache Phoenix vs. Hawkular Metrics vs. OpenQM vs. PostGIS vs. Trafodion

System Properties Comparison Apache Phoenix vs. Hawkular Metrics vs. OpenQM vs. PostGIS vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

QpenQM is a high-performance, self-tuning, multi-value DBMS

Spatial extension of PostgreSQL

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

phoenix.apache.org

www.hawkular.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

postgis.net

trafodion.apache.org

Technical documentation

phoenix.apache.org

www.hawkular.org/hawkular-metrics/docs/user-guide

postgis.net/documentation

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

Community supported by Red Hat

Rocket Software, originally Martin Phillips

Apache Software Foundation, originally developed by HP

Initial release

2014

1993

2005

2014

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

3.4-12

3.4.2, February 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

GPL v2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, Java

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

with some exceptions

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC

HTTP REST

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

Go
Java
Python
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Java Stored Procedures

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

based on PostgreSQL

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

yes

based on PostgreSQL

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Access rights can be defined down to the item level

yes

based on PostgreSQL

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, Microsoft

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Azure HDInsight Analytics Platform Now Supports Apache Hadoop 3.0
18 April 2019, eWeek

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5 June 2019, DevClass

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2 November 2016, KDnuggets

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14 July 2014, Datanami

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

Apache Software Foundation Releases its 2019 Fiscal Year Report
17 August 2019, Open Source For You

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