DBMS > OpenQM vs. OushuDB vs. RocksDB

System Properties Comparison OpenQM vs. OushuDB vs. RocksDB

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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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Multivalue DBMS

Relational DBMS

Key-value store

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

Score	0.33
Rank	#286	Overall
	#10	Multivalue DBMS

Score	0.09
Rank	#357	Overall
	#154	Relational DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

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

www.oushu.com/product/oushuDB

rocksdb.org

Technical documentation

www.oushu.com/documentation

github.com/facebook/rocksdb/wiki

Developer

Rocket Software, originally Martin Phillips

Oushu

Facebook, Inc.

Initial release

1993

2013

Current release

3.4-12

4.0.1, August 2020

8.11.4, April 2024

License

Commercial or Open Source

Open Source

GPLv2, extended commercial license available

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

yes

with some exceptions

yes

schema-free

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

C++ API
Java API

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

C
C++

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

horizontal partitioning

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

yes

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 rights can be defined down to the item level

Kerberos, SSL and role based access

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