DBMS > BigchainDB vs. BigObject vs. FatDB vs. JanusGraph vs. PouchDB

System Properties Comparison BigchainDB vs. BigObject vs. FatDB vs. JanusGraph vs. PouchDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

Analytic DBMS for real-time computations and queries

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A Graph DBMS optimized for distributed clusters

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

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store

Relational DBMS

a hierachical model (tree) can be imposed

Document store
Key-value store

Graph DBMS

Document store

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.bigobject.io

docs.janusgraph.org

pouchdb.com/guides

Developer

BigObject, Inc.

FatCloud

Linux Foundation; originally developed as Titan by Aurelius

Apache Software Foundation

Initial release

2016

2015

2012

2017

2012

Current release

0.6.3, February 2023

7.1.1, June 2019

License

Commercial or Open Source

Open Source

AGPL v3

commercial

free community edition available

commercial

Open Source

Apache 2.0

Open Source

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

Java

JavaScript

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Windows

Linux
OS X
Unix
Windows

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

Data scheme

schema-free

yes

schema-free

yes

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 DML and DDL statements

Via inetgration in SQL Server

APIs and other access methods

CLI Client
RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Clojure
Java
Python

JavaScript

Server-side scripts

Stored procedures

Lua

yes

via applications

yes

View functions in JavaScript

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

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

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

selectable replication factor

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

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

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

User concepts

Access control

yes

Can implement custom security layer via applications

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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