DBMS > Badger vs. BoltDB vs. CouchDB vs. DataFS

System Properties Comparison Badger vs. BoltDB vs. CouchDB vs. DataFS

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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.

Primary database model

Key-value store

Document store

Object oriented 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	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Website

github.com/dgraph-io/badger

github.com/boltdb/bolt

couchdb.apache.org

newdatabase.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.couchdb.org/en/stable

dev.mobiland.com/Overview.xsp

Developer

DGraph Labs

Apache Software Foundation

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

Mobiland AG

Initial release

2017

2013

2005

2018

Current release

3.3.3, December 2023

1.1.263, October 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Apache version 2

commercial

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

Erlang

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Android
BSD
Linux
OS X
Solaris
Windows

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)

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

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
Proprietary client DLL
WinRT client

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

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

none

Sharding

improved architecture with release 2.0

Proprietary Sharding system

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source 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

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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.

User concepts

Access control

Access rights for users can be defined per database

Windows-Profile

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More resources

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