DBMS > JaguarDB vs. OpenQM vs. Postgres-XL

System Properties Comparison JaguarDB vs. OpenQM vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Key-value store
Vector DBMS

Multivalue DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

www.jaguardb.com

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

www.postgres-xl.org

Technical documentation

www.jaguardb.com/support.html

www.postgres-xl.org/documentation

Developer

DataJaguar, Inc.

Rocket Software, originally Martin Phillips

Initial release

2015

1993

2014

since 2012, originally named StormDB

Current release

3.3 July 2023

3.4-12

10 R1, October 2018

License

Commercial or Open Source

Open Source

GPL V3.0

Open Source

GPLv2, extended commercial license available

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

the server part. Clients available in other languages

Server operating systems

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
macOS

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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.

User concepts

Access control

rights management via user accounts

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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