DBMS > Bangdb vs. CouchDB vs. EventStoreDB vs. Quasardb

System Properties Comparison Bangdb vs. CouchDB vs. EventStoreDB vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Distributed, high-performance timeseries database

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store

Event Store

Time Series DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Website

Technical documentation

docs.bangdb.com

docs.couchdb.org/en/stable

developers.eventstore.com

doc.quasar.ai/master

Developer

Sachin Sinha, BangDB

Apache Software Foundation

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

Event Store Limited

quasardb

Initial release

2012

2005

2012

2009

Current release

BangDB 2.0, October 2021

3.3.3, December 2023

21.2, February 2021

3.14.1, January 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache version 2

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

C, C++

Erlang

C++

Server operating systems

Linux

Android
BSD
Linux
OS X
Solaris
Windows

Linux
Windows

BSD
Linux
OS X
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

integer and binary

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

secondary, composite, nested, reverse, geospatial

yes

via views

yes

with tags

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP/JSON API

HTTP API

Supported programming languages

C
C#
C++
Java
Python

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

improved architecture with release 2.0

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

by using LevelDB

In-memory capabilities

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

yes, run db with in-memory only mode

yes

Transient mode

User concepts

Access control

yes (enterprise version only)

Access rights for users can be defined per database

Cryptographically strong user authentication and audit trail

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