DBMS > Linter vs. MonetDB

System Properties Comparison Linter vs. MonetDB

Please select another system to include it in the comparison.

Our visitors often compare Linter and MonetDB with PostgreSQL, MySQL and ClickHouse.

Editorial information provided by DB-Engines

Name

Description

RDBMS for high security requirements

A relational database management system that stores data in columns

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.00
Rank	#382	Overall
	#155	Relational DBMS

Score	1.57
Rank	#138	Overall
	#62	Relational DBMS

Website

linter.ru

www.monetdb.org

Technical documentation

www.monetdb.org/Documentation

Developer

relex.ru

MonetDB BV

Initial release

1990

2004

Current release

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

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

C and C++

Server operating systems

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication available in experimental status

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R — Part I
6 April 2018, Data Science Central

Figure 1: MonetDB: a BAT Algebra Machine
7 September 2018, ResearchGate

Test of Time Award for paper on vectorized execution
16 January 2024, Centrum Wiskunde & Informatica (CWI)

ff and Too-Big-for-Memory Data in R — Part III
7 February 2018, Data Science Central

Forget about SQLite, Use DuckDB Instead – And Thank Me Later
16 March 2023, Towards Data Science

provided by Google News

Share this page