DBMS > MonetDB vs. PostgreSQL vs. SQLite vs. TimesTen

System Properties Comparison MonetDB vs. PostgreSQL vs. SQLite vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

A relational database management system that stores data in columns

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Widely used embeddable, in-process RDBMS

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.monetdb.org

www.postgresql.org

www.sqlite.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.monetdb.org/Documentation

www.postgresql.org/docs

www.sqlite.org/docs.html

docs.oracle.com/database/timesten-18.1

Developer

MonetDB BV

PostgreSQL Global Development Group

www.postgresql.org/developer

Dwayne Richard Hipp

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2004

1989

1989: Postgres, 1996: PostgreSQL

2000

1998

Current release

Dec2023 (11.49), December 2023

16.3, May 2024

3.46.0 (23 May 2024), May 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Mozilla Public License 2.0

Open Source

BSD

Open Source

Public Domain

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

server-less

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

standard with numerous extensions

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes, in SQL, C, R

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding via remote tables

partitioning by range, list and (since PostgreSQL 11) by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Source-replica replication

other methods possible by using 3rd party extensions

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

via file-system locks

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

3rd parties

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