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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Firebase Authentication vs MongoDB

Firebase Authentication vs MongoDB

OverviewDecisionsComparisonAlternatives

Overview

MongoDB
MongoDB
Stacks96.6K
Followers82.0K
Votes4.1K
GitHub Stars27.7K
Forks5.7K
Firebase Authentication
Firebase Authentication
Stacks533
Followers610
Votes55

Firebase Authentication vs MongoDB: What are the differences?

Introduction

In this article, we will explore the key differences between Firebase Authentication and MongoDB for website development.

  1. Scalability and Performance: Firebase Authentication and MongoDB differ significantly in terms of scalability and performance. Firebase Authentication is a managed service that offers high scalability and seamless integration with other Firebase features. It automatically scales to handle millions of users without requiring manual intervention. On the other hand, MongoDB is a NoSQL database that can be scalable through sharding, but it requires more manual configuration and monitoring to handle high volumes of data and user requests efficiently.

  2. Schema and Query Flexibility: Another crucial difference between Firebase Authentication and MongoDB is the schema and query flexibility. Firebase Authentication offers a straightforward and predefined user authentication schema, making it easy to integrate authentication functionality into the website. It also provides basic querying capabilities for common user attributes. In contrast, MongoDB is a schema-less database, enabling developers to store unstructured data without predefined schemas. Additionally, MongoDB offers a powerful querying language and flexible indexing options, allowing complex querying and high customization.

  3. Real-time Data Sync: Firebase Authentication is part of the Firebase suite, which includes Firebase Realtime Database and Cloud Firestore. This integration provides seamless real-time data sync capabilities, enabling instant updates and synchronization across multiple devices. This feature makes Firebase Authentication an excellent choice for applications requiring real-time collaboration and live data updates. MongoDB, on the other hand, does not provide built-in real-time data sync functionalities and requires additional tools or frameworks to achieve real-time updates.

  4. Security Features: Both Firebase Authentication and MongoDB offer robust security features, but they differ in their security implementations. Firebase Authentication provides ready-to-use authentication mechanisms like email/password, social media logins, and phone authentication, along with OAuth integration options. It also supports multi-factor authentication and user role management. MongoDB, on the other hand, offers flexible security controls through role-based access control (RBAC), field-level access control (FLAC), and transport encryption. Developers have more control over the security implementation in MongoDB but may require additional customizations and configurations.

  5. Offline Support: Firebase Authentication, being a part of the Firebase suite, comes with offline support out of the box. This means that even if the website loses connectivity, Firebase Authentication can continue to authenticate users locally and allow basic functionality until the connection is restored. MongoDB, being a database, does not provide native offline support. Offline caching or syncing mechanisms would need to be implemented separately for offline functionalities in a MongoDB-backed website.

  6. Cost Structure: Firebase Authentication and MongoDB have different cost structures. Firebase Authentication offers a free tier with limited usage and additional paid plans based on the number of monthly active users. It also provides a pay-as-you-go pricing model for specific features like phone authentication. MongoDB Pricing is based on factors such as storage, data transfer, and compute resources consumed. It offers a free tier for development purposes, but pricing can increase significantly for higher usage levels and additional features like automatic scaling, backups, and managed services.

In Summary, Firebase Authentication offers seamless scalability, a predefined authentication schema, real-time data sync, and offline support, along with a managed Firebase suite integration, while MongoDB provides more flexibility in terms of schema design, querying capabilities, security implementation, and cost structure.

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Advice on MongoDB, Firebase Authentication

George
George

Student

Mar 18, 2020

Needs adviceonPostgreSQLPostgreSQLPythonPythonDjangoDjango

Hello everyone,

Well, I want to build a large-scale project, but I do not know which ORDBMS to choose. The app should handle real-time operations, not chatting, but things like future scheduling or reminders. It should be also really secure, fast and easy to use. And last but not least, should I use them both. I mean PostgreSQL with Python / Django and MongoDB with Node.js? Or would it be better to use PostgreSQL with Node.js?

*The project is going to use React for the front-end and GraphQL is going to be used for the API.

Thank you all. Any answer or advice would be really helpful!

620k views620k
Comments
Ido
Ido

Mar 6, 2020

Decided

My data was inherently hierarchical, but there was not enough content in each level of the hierarchy to justify a relational DB (SQL) with a one-to-many approach. It was also far easier to share data between the frontend (Angular), backend (Node.js) and DB (MongoDB) as they all pass around JSON natively. This allowed me to skip the translation layer from relational to hierarchical. You do need to think about correct indexes in MongoDB, and make sure the objects have finite size. For instance, an object in your DB shouldn't have a property which is an array that grows over time, without limit. In addition, I did use MySQL for other types of data, such as a catalog of products which (a) has a lot of data, (b) flat and not hierarchical, (c) needed very fast queries.

575k views575k
Comments
Mike
Mike

Mar 20, 2020

Needs advice

We Have thousands of .pdf docs generated from the same form but with lots of variability. We need to extract data from open text and more important - from tables inside the docs. The output of Couchbase/Mongo will be one row per document for backend processing. ADOBE renders the tables in an unusable form.

241k views241k
Comments

Detailed Comparison

MongoDB
MongoDB
Firebase Authentication
Firebase Authentication

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

It provides backend services, easy-to-use SDKs, and ready-made UI libraries to authenticate users to your app. It supports authentication using passwords, phone numbers, popular federated identity providers like Google,

Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS
-
Statistics
GitHub Stars
27.7K
GitHub Stars
-
GitHub Forks
5.7K
GitHub Forks
-
Stacks
96.6K
Stacks
533
Followers
82.0K
Followers
610
Votes
4.1K
Votes
55
Pros & Cons
Pros
  • 829
    Document-oriented storage
  • 594
    No sql
  • 554
    Ease of use
  • 465
    Fast
  • 410
    High performance
Cons
  • 6
    Very slowly for connected models that require joins
  • 3
    Not acid compliant
  • 2
    Proprietary query language
Pros
  • 12
    Completely Free
  • 8
    Native App + Web integrations
  • 8
    Email/Password
  • 7
    Passwordless
  • 6
    Works seemlessly with other Firebase Services
Cons
  • 6
    Heavy webpack

What are some alternatives to MongoDB, Firebase Authentication?

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

Auth0

Auth0

A set of unified APIs and tools that instantly enables Single Sign On and user management to all your applications.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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