DBMS > Badger vs. Infobright vs. PouchDB vs. VoltDB

System Properties Comparison Badger vs. Infobright vs. PouchDB vs. VoltDB

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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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

JavaScript DBMS with an API inspired by CouchDB

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

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

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

github.com/dgraph-io/badger

ignitetech.com/softwarelibrary/infobrightdb

pouchdb.com

www.voltdb.com

Technical documentation

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

pouchdb.com/guides

docs.voltdb.com

Developer

DGraph Labs

Ignite Technologies Inc.; formerly InfoBright Inc.

Apache Software Foundation

VoltDB Inc.

Initial release

2017

2005

2012

2010

Current release

7.1.1, June 2019

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

JavaScript

Java, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

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

Linux
OS X

for development

Data scheme

schema-free

yes

schema-free

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

Knowledge Grid Technology used instead

yes

via views

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Users and roles with access to stored procedures

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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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