DBMS > CouchDB vs. Drizzle vs. Microsoft SQL Server vs. MonetDB

System Properties Comparison CouchDB vs. Drizzle vs. Microsoft SQL Server vs. MonetDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

Primary database model

Document store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Website

couchdb.apache.org

www.microsoft.com/en-us/sql-server

www.monetdb.org

Technical documentation

docs.couchdb.org/en/stable

learn.microsoft.com/en-US/sql/sql-server

www.monetdb.org/Documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Drizzle project, originally started by Brian Aker

Microsoft

MonetDB BV

Initial release

2005

2008

1989

2004

Current release

3.3.3, December 2023

7.2.4, September 2012

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GNU GPL

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Erlang

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

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

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL 2003 with some extensions

APIs and other access methods

RESTful HTTP/JSON API

JDBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

C
C++
Java
PHP

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

View functions in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes, in SQL, C, R

Triggers

yes

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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

Access rights for users can be defined per database

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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