DBMS > Bangdb vs. CouchDB vs. Firebase Realtime Database vs. YottaDB

System Properties Comparison Bangdb vs. CouchDB vs. Firebase Realtime Database vs. YottaDB

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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.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

A fast and solid embedded Key-value store

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store

Key-value store

Secondary database models

Spatial DBMS

using the Geocouch extension

Relational DBMS

using the Octo plugin

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	13.60
Rank	#39	Overall
	#6	Document stores

Score	0.21
Rank	#309	Overall
	#43	Key-value stores

Website

bangdb.com

couchdb.apache.org

firebase.google.com/products/realtime-database

yottadb.com

Technical documentation

docs.bangdb.com

docs.couchdb.org/en/stable

firebase.google.com/docs/database

yottadb.com/resources/documentation

Developer

Sachin Sinha, BangDB

Apache Software Foundation

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

Google

acquired by Google 2014

YottaDB, LLC

Initial release

2012

2005

2012

2001

Current release

BangDB 2.0, October 2021

3.3.3, December 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache version 2

commercial

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Erlang

Server operating systems

Linux

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Docker
Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

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

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

secondary, composite, nested, reverse, geospatial

yes

via views

yes

SQL

Support of SQL

SQL like support with command line tool

by using the Octo plugin

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP/JSON API

Android
iOS
JavaScript API
RESTful HTTP API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

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

Java
JavaScript
Objective-C

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

View functions in JavaScript

limited functionality with using 'rules'

Triggers

yes, Notifications (with Streaming only)

yes

Callbacks are triggered when data changes

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

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

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

yes

optimistic locking

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

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

User concepts

Access control

yes (enterprise version only)

Access rights for users can be defined per database

yes, based on authentication and database rules

Users and groups based on OS-security mechanisms

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More resources

DB-Engines blog posts

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