DBMS > LeanXcale vs. MonetDB vs. OpenQM vs. Valentina Server

System Properties Comparison LeanXcale vs. MonetDB vs. OpenQM vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A relational database management system that stores data in columns

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

Object-relational database and reports server

Primary database model

Key-value store
Relational DBMS

Relational 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	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.leanxcale.com

www.monetdb.org

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

www.valentina-db.net

Technical documentation

www.monetdb.org/Documentation

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

LeanXcale

MonetDB BV

Rocket Software, originally Martin Phillips

Paradigma Software

Initial release

2015

2004

1993

1999

Current release

Dec2023 (11.49), December 2023

3.4-12

5.7.5

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

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.

Implementation language

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Windows

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

yes

through Apache Derby

yes

SQL 2003 with some extensions

yes

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ODBC

Supported programming languages

C
Java
Scala

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes, in SQL, C, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding via remote tables

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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