DBMS > MySQL vs. OpenQM vs. Solr vs. TempoIQ vs. Trafodion

System Properties Comparison MySQL vs. OpenQM vs. Solr vs. TempoIQ vs. Trafodion

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

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

Description

Widely used open source RDBMS

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

A widely used distributed, scalable search engine based on Apache Lucene

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

www.mysql.com

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

solr.apache.org

tempoiq.com (offline)

trafodion.apache.org

Technical documentation

dev.mysql.com/doc

solr.apache.org/resources.html

trafodion.apache.org/documentation.html

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Rocket Software, originally Martin Phillips

Apache Software Foundation

TempoIQ

Apache Software Foundation, originally developed by HP

Initial release

1995

1993

2006

2012

2014

Current release

8.4.0, April 2024

3.4-12

9.6.1, May 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPLv2, extended commercial license available

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

Java

C++, Java

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

yes

with some exceptions

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

Solr Parallel SQL Interface

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
RESTful HTTP/JSON API

HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Java plugins

Java Stored Procedures

Triggers

yes

User configurable commands triggered on index changes

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

Access rights can be defined down to the item level

yes

simple authentication-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.