DBMS > Couchbase vs. Firebase Realtime Database vs. Graph Engine vs. Newts vs. PouchDB

System Properties Comparison Couchbase vs. Firebase Realtime Database vs. Graph Engine vs. Newts vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Time Series DBMS based on Cassandra

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store

Graph DBMS
Key-value store

Time Series DBMS

Document store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

www.couchbase.com

firebase.google.com/products/realtime-database

www.graphengine.io

opennms.github.io/newts

pouchdb.com

Technical documentation

docs.couchbase.com

firebase.google.com/docs/database

www.graphengine.io/docs/manual

github.com/OpenNMS/newts/wiki

pouchdb.com/guides

Developer

Couchbase, Inc.

Google

acquired by Google 2014

Microsoft

OpenNMS Group

Apache Software Foundation

Initial release

2011

2012

2010

2014

2012

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Go and Erlang

.NET and C

Java

JavaScript

Server operating systems

Linux
OS X
Windows

hosted

.NET

Linux
OS X
Windows

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

Data scheme

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++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API

HTTP REST
Java API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java
JavaScript
Objective-C

C#
C++
F#
Visual Basic

Java

JavaScript

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

limited functionality with using 'rules'

yes

View functions in JavaScript

Triggers

yes

via the TAP protocol

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

horizontal partitioning

Sharding

based on Cassandra

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

based on Cassandra

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

yes, based on authentication and database rules

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