DBMS > CouchDB vs. DataFS vs. RocksDB vs. SWC-DB

System Properties Comparison CouchDB vs. DataFS vs. RocksDB vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Graph DBMS

Time Series DBMS

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

couchdb.apache.org

newdatabase.com

rocksdb.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.couchdb.org/en/stable

dev.mobiland.com/Overview.xsp

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

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

Mobiland AG

Facebook, Inc.

Alex Kashirin

Initial release

2005

2018

2013

2020

Current release

3.3.3, December 2023

1.1.263, October 2022

9.2.1, May 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

BSD

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Windows

Linux

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

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

via views

SQL

Support of SQL

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
Proprietary client DLL
WinRT client

C++ API
Java API

Proprietary protocol
Thrift

Supported programming languages

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

.Net
C
C#
C++
VB.Net

C
C++
Go
Java
Perl
Python
Ruby

C++

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Proprietary Sharding system

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

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

yes

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

Windows-Profile

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