DBMS > Google Cloud Firestore vs. MongoDB

System Properties Comparison Google Cloud Firestore vs. MongoDB

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Our visitors often compare Google Cloud Firestore and MongoDB with Amazon DynamoDB, Google Cloud Datastore and Redis.

Editorial information provided by DB-Engines

Name

Description

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store

Secondary database models

Search engine info

integrated Lucene index, currently in MongoDB Atlas only.

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

Score	7.52
Rank	#49	Overall
	#9	Document stores

Score	437.08
Rank	#5	Overall
	#1	Document stores

Website

firebase.google.com/products/firestore

www.mongodb.com

Technical documentation

firebase.google.com/docs/firestore

docs.mongodb.com/manual

Developer

Google

MongoDB, Inc

Initial release

2017

2009

Current release

4.2.7, May 2020

License

Commercial or Open Source

commercial

Open Source info

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Cloud-based only info

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links) info

Database as a Service

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

MongoDB Atlas: Deploy a fully managed cloud database on-demand and ready for use in minutes. Available on AWS, Azure, and GCP.

Implementation language

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Data scheme

schema-free

schema-free info

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

XML support info

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

SQL

Support of SQL

Read-only SQL queries via the MongoDB Connector for BI

APIs and other access methods

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Actionscript info

inofficial driver
C
C#
C++
Clojure info

inofficial driver
ColdFusion info

inofficial driver
D info

inofficial driver
Dart info

inofficial driver
Delphi info

inofficial driver
Erlang
Go
Groovy info

inofficial driver
Haskell
Java
JavaScript
Lisp info

inofficial driver
Lua info

inofficial driver
MatLab info

inofficial driver
Perl
PHP
PowerShell info

inofficial driver
Prolog info

inofficial driver
Python
R info

inofficial driver
Ruby
Scala
Smalltalk info

inofficial driver

Server-side scripts info

Stored procedures

yes, Firebase Rules & Cloud Functions

JavaScript

Triggers

yes, with Cloud Functions

yes

in MongoDB Atlas only

Partitioning methods info

Methods for storing different data on different nodes

Sharding

partitioned by hashed, ranged, or zoned sharding keys

Replication methods info

Methods for redundantly storing data on multiple nodes

Master-master replication

Master-slave replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts info

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency info

can be individually decided for each write operation

Foreign keys info

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts info

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

yes

Multi-document ACID Transactions with snapshot isolation

Concurrency info

Support for concurrent manipulation of data

yes

Durability info

Support for making data persistent

yes

optional

In-memory capabilities info

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

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts info

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB is the leading modern, general purpose data platform, designed to unleash...
» more

Competitive advantages

The MongoDB Data Platform can be used by developers building OLTP and analytical...
» more

Typical application scenarios

Internet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
» more

Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

70 million downloads (growing at more than 30 thousand downloads per day). 15,000+...
» more

Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.