Choosing the right database service before start developing applications is a good idea. But developers often make this mistake by not selecting the right database. To choose the right platform, developers need to understand what every database has to offer.
Before starting your project, you should have a clear idea about your audience’s geographics and demographics. If you create direct consumer-facing applications, you should keep in mind that it will have millions of traffic on your website.
If your backend is not strong enough to take on such traffic, your app will eventually crash and cause a service meltdown. In addition, if your database is not created or set up correctly, it will become an enormous problem for your application to handle the traffic.
What is Google Firebase
Google Firebase is a platform for creating web and mobile applications fast, reliable, and secure. With Firebase, you can build apps and do not worry about infrastructure at all.
Firebase’s real-time database is an excellent choice for apps that need to handle data in real-time across multiple devices. The database service of Firebase is called Cloud Firestore. It works in nearly real-time, fetching changes from your database as they happen.
Advantages of Google Firebase
- Firebase has rich client library support.
- Firebase is a comprehensive set of security rules.
- Firebase is easy to use backend database service.
What is MongoDB
MongoDB is a cross-platform document-oriented database program. Firebase and MongoDB are working to create robust, convenient, and scalable modern database platforms for web and app developers.
Advantages of MongoDB
- MongoDB is a schemaless database because one collection holds different documents.
- MongoDB has no complex joins.
- MongoDB is straightforward to scale.
- Mapping of application objects to database objects is not needed in MongoDB.
The similarity between Firebase and MongoDB
- Firebase and MongoDB are post-relational databases with related JSON-like document data models and schemas.
- Firebase and MongoDB support developers to get started fast and articulate their data structures as they build.
- Firebase and MongoDB separate data into “collections” for easy distribution across scalable database clusters.
- Firebase and MongoDB provide single-purpose NoSQL solutions to their customers.
- Firebase and MongoDB have well-prepared technical documentation that eases the work with offered services and makes them more accessible for users.
- Firebase and MongoDB are both free for beginners.
Firebase vs. MongoDB: The Difference
- Firebase is self-hosted; in MongoDB, you can use Windows, Linux, or any server to host. You can even install it on localhost, which you can’t do in Firebase. In addition, MongoDB can be hosted on-premise or in the cloud, such as MongoDB Atlas, or self-managed cloud MongoDB, while Firebase is purely a cloud database service.
- Firebase is more suitable for small to medium-sized applications where MongoDB can be used in small, medium, large, and enterprise-level applications.
- Firebase supports C++, Javascript, Java, C, PHP, Node.js, Swift, whereas MongoDB supports Node.js, JavaScript, PHP, Python, C, C++.
- When it comes to performance, MongoDB is far superior compared to Firebase because MongoDB has a document database known for high performance.
- Firebase has less security compared to MongoDB.
- Firebase can be used for its services such as user authentication, analytics, crashlytics, storage, and cloud messaging. In contrast, MongoDB can be used for big data, content delivery, a data hub, and user data management.
- Firebase requires little to no technical knowledge to start working on your product, whereas MongoDB requires basic database management understanding plus JSON data type. You also need to learn how to use efficient queries to store, fetch, and change the data into the MongoDB database.
- Firebase has limited querying capabilities, whereas MongoDB has extensive database query support, which can fetch almost any kind of data you want for your application.
- Firebase data storage is inconvenient, and you will use the Realtime Database as your primary storage. MongoDB has good storage capacity because the maximum BSON document size is 16 megabytes. To store documents larger than the maximum size, MongoDB provides the GridFS API.
- Firebase doesn’t provide the equivalent abilities for Android and iOS apps. Firebase is still more of an Android-centered service because of Google, and it’s the Android system that gets most of the dedicated services and facilities. Whereas, when you are developing Android or iOS apps, if your backend language supports MongoDB, you can use MongoDB for both Android and iOS platforms.
- Major companies that used Firebase are Venmo, Lyft, Duolingo, Shazam, and Alibaba. Major companies that use the MongoDB database are Adobe, SEGA, Verizon, EA Games, etc.
Firebase vs. MongoDB: Complete Comparison Overview
Firebase | MongoDB | |
Performance | Compare to MongoDB, not much high performance. | High-performance databases for enterprise-level applications. |
Server Infrastructure | It is self-hosted and provides. | It provides on-premise and cloud solutions such as MongoDB Atlas. |
Supported Languages | JavaScript, PHP, C, C++, Java, Android, iOS | Node.js, JavaScript, PHP, Python, Java, C# |
Security | Firebase is less secured | MongoDB is more secure and scalable. |
Querying limit | Firebase has limited querying capabilities. | MongoDB has unlimited querying capabilities |
Learning curve | Firebase is easy to start, learn, and implement and does not require advanced knowledge. | MongoDB requires background database knowledge, plus no SQL knowledge, plus JSON Data types and how it works. |
That is it for Firebase vs. MongoDB difference.

Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Machine Learning frameworks like PyTorch and Tensorflow is a testament to his versatility and commitment to the craft.