DBMS > OpenQM vs. OushuDB vs. Ultipa

System Properties Comparison OpenQM vs. OushuDB vs. Ultipa

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Multivalue DBMS

Relational DBMS

Graph DBMS

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

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

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

www.oushu.com/product/oushuDB

www.ultipa.com

Technical documentation

www.oushu.com/documentation

www.ultipa.com/document

Developer

Rocket Software, originally Martin Phillips

Oushu

Ultipa

Initial release

1993

2019

Current release

3.4-12

4.0.1, August 2020

License

Commercial or Open Source

Open Source

GPLv2, extended commercial license available

commercial

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.

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

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

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

C
C++

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

User concepts

Access control

Access rights can be defined down to the item level

Kerberos, SSL and role based access

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

China's answer to Snowflake is shaping as data demands upgrade
8 September 2021, PingWest

provided by Google News

High-performance computing's role in real-time graph analytics - DataScienceCentral.com
30 January 2024, Data Science Central

provided by Google News

Share this page