DBMS > CouchDB vs. Datomic vs. mSQL vs. MySQL vs. ToroDB

System Properties Comparison CouchDB vs. Datomic vs. mSQL vs. MySQL vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it 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.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used open source RDBMS

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Document store

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

couchdb.apache.org

www.datomic.com

hughestech.com.au/products/msql

www.mysql.com

github.com/torodb/server

Technical documentation

docs.couchdb.org/en/stable

docs.datomic.com

dev.mysql.com/doc

Developer

Apache Software Foundation

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

Cognitect

Hughes Technologies

Oracle

since 2010, originally MySQL AB, then Sun

8Kdata

Initial release

2005

2012

1994

1995

2016

Current release

3.3.3, December 2023

1.0.7075, December 2023

4.4, October 2021

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

limited edition free

commercial

free licenses can be provided

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

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Implementation language

Erlang

Java, Clojure

C and C++

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

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

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

Clojure
Java

C
C++
Delphi
Java
Perl
PHP
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Transaction Functions

yes

proprietary syntax

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

But extensive use of caching in the application peers

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

But extensive use of caching in the application peers

none

Multi-source replication
Source-replica replication

Source-replica replication

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

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

atomic operations within a single document possible

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

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