DBMS > Firebase Realtime Database vs. LeanXcale vs. mSQL vs. Newts vs. PouchDB

System Properties Comparison Firebase Realtime Database vs. LeanXcale vs. mSQL vs. Newts vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

mSQL (Mini SQL) is a simple and lightweight RDBMS

Time Series DBMS based on Cassandra

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Document store

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

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Website

firebase.google.com/products/realtime-database

www.leanxcale.com

hughestech.com.au/products/msql

opennms.github.io/newts

pouchdb.com

Technical documentation

firebase.google.com/docs/database

github.com/OpenNMS/newts/wiki

pouchdb.com/guides

Developer

Google

acquired by Google 2014

LeanXcale

Hughes Technologies

OpenNMS Group

Apache Software Foundation

Initial release

2012

2015

1994

2014

2012

Current release

4.4, October 2021

7.1.1, June 2019

License

Commercial or Open Source

commercial

free licenses can be provided

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

Java

JavaScript

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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

yes

through Apache Derby

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC

HTTP REST
Java API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Java
JavaScript
Objective-C

C
Java
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

Java

JavaScript

Server-side scripts

Stored procedures

limited functionality with using 'rules'

View functions in JavaScript

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

User concepts

Access control

yes, based on authentication and database rules

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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Recent citations in the news

Realtime vs Cloud Firestore: Which Firebase Database to Choose
8 March 2024, Appinventiv

Misconfigured Firebase instances leaked 19 million plaintext passwords
19 March 2024, BleepingComputer

Don't be like these 900+ websites and expose millions of passwords via Firebase
18 March 2024, The Register

Misconfigured firebase: A real-time cyber threat
18 January 2024, Atos

Google launches Firebase Genkit, a new open source framework for building AI-powered apps
14 May 2024, TechCrunch

provided by Google News

Create Offline Web Apps Using Service Workers & PouchDB
7 March 2017, SitePoint

Getting Started with PouchDB Client-Side JavaScript Database
7 September 2016, SitePoint

Building an Offline First App with PouchDB
10 March 2014, SitePoint

provided by Google News

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