DBMS > OpenQM vs. UniData,UniVerse vs. Vitess

System Properties Comparison OpenQM vs. UniData,UniVerse vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

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

MultiValue database and application server with SQL mapping layer and meta database capabilities

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Multivalue DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

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

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

vitess.io

Technical documentation

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

vitess.io/docs

Developer

Rocket Software, originally Martin Phillips

Rocket Software

The Linux Foundation, PlanetScale

Initial release

1993

1985

2013

Current release

3.4-12

15.0.2, December 2022

License

Commercial or Open Source

Open Source

GPLv2, extended commercial license available

commercial

Open Source

Apache Version 2.0, commercial licenses available

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

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Docker
Linux
macOS

Data scheme

yes

with some exceptions

schema-free

yes

Typing

predefined data types such as float or date

optional

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

with proprietary extensions

APIs and other access methods

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Basic

U2 Basic
C
Java

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

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

U2 Basic

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

configurable

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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 rights can be defined down to the item level

Access rights according to SQL-standard and operating system based

Users with fine-grained authorization concept

no user groups or roles

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