DBMS > MonetDB vs. PouchDB vs. SQLite vs. Teradata Aster vs. Valentina Server

System Properties Comparison MonetDB vs. PouchDB vs. SQLite vs. Teradata Aster vs. Valentina Server

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

A relational database management system that stores data in columns

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Platform for big data analytics on multistructured data sources and types

Object-relational database and reports server

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

Technical documentation

www.monetdb.org/Documentation

pouchdb.com/guides

www.sqlite.org/docs.html

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

Developer

MonetDB BV

Apache Software Foundation

Dwayne Richard Hipp

Teradata

Paradigma Software

Initial release

2004

2012

2000

2005

1999

Current release

Dec2023 (11.49), December 2023

7.1.1, June 2019

3.45.3 (15 April 2024), April 2024

5.7.5

License

Commercial or Open Source

Open Source

Mozilla Public License 2.0

Open Source

Public Domain

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

JavaScript

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

server-less

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

dynamic column types

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL 2003 with some 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

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
OLE DB

ODBC

Supported programming languages

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

JavaScript

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#
C++
Java
Python
R

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

Server-side scripts

Stored procedures

yes, in SQL, C, R

View functions in JavaScript

R packages

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding via remote tables

Sharding

with a proxy-based framework, named couchdb-lounge

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual 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 using IndexedDB, WebSQL or LevelDB as backend

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

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