DBMS > BigchainDB vs. CouchDB vs. DataFS vs. JanusGraph

System Properties Comparison BigchainDB vs. CouchDB vs. DataFS vs. JanusGraph

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Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Primary database model

Document store

Object oriented DBMS

Graph DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Graph DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Website

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.couchdb.org/en/stable

dev.mobiland.com/Overview.xsp

docs.janusgraph.org

Developer

Apache Software Foundation

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

Mobiland AG

Linux Foundation; originally developed as Titan by Aurelius

Initial release

2016

2005

2018

2017

Current release

3.3.3, December 2023

1.1.263, October 2022

1.0.0, October 2023

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

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

Python

Erlang

Java

Server operating systems

Linux

Android
BSD
Linux
OS X
Solaris
Windows

Windows

Linux
OS X
Unix
Windows

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)

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

APIs and other access methods

CLI Client
RESTful HTTP API

RESTful HTTP/JSON API

.NET Client API
Proprietary client DLL
WinRT client

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

Clojure
Java
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Triggers

yes

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Proprietary Sharding system

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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,with MongoDB ord RethinkDB

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

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

User concepts

Access control

yes

Access rights for users can be defined per database

Windows-Profile

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

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Recent citations in the news

Using BigchainDB: A Database with Blockchain Characteristics
20 January 2022, Open Source For You

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26 August 2017, Blockchain Council

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2 March 2017, ZDNet

BigchainDB: A Popular and Powerful Database for Blockchain
9 September 2019, Open Source For You

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