With numerous database systems available in the market, choosing a suitable database is crucial for your business. In case you choose a database that doesn’t meet your application requirements, it would be costly and overburdened to migrate your database. Whichever platform you choose, it is important that it should be robust, usable, scalable, and support your application development environment.
Nowadays, many organizations prefer to choose dynamic schema or NoSQL databases due to their ability to manage a large volume of unstructured data. Firebase platform and MongoDB are two popular NoSQL services when it comes to developing web and mobile applications. Both can handle real-time data and operate best with massive volumes of data, and this article will help you understand the key features and differences between the MongoDB vs. Firebase platforms.
Backed by Google, Firebase is an application development platform that helps developers to build and manage Android, iOS, and Web applications. However, the platform is designed especially for mobile application development that includes authentication, hosting, real-time analytics, and test-lab functionality. The data is stored as JSON objects and synced continuously for real-time usage.
Firebase has two types of databases: Realtime Database and Cloud Firestore.
- RealTime Database: Firebase's Realtime Database lets you store and sync real-time data between users as it is a cloud-hosted NoSQL database. It uses data synchronization, which lets the connected devices receive updated data within milliseconds. Apart from real-time synchronization, it also works in offline mode. This type of database is specifically suitable for banking, scientific data analysis, medical records, accounting, etc.
- Cloud Firestore Database: Developed by Firebase and Google Cloud, Cloud Firestore is a NoSQL cloud database used to store and sync data for a client- and server-side development.
For a full comparison of RealTime Database and Cloud Firestore, check out this article.
Some of the key features of Firebase that make it unique are:
- Authentication: Firebase authentication provides easy sign-in with various platforms. It supports phone auth, Gmail login, Twitter, GitHub, Facebook, and more. This feature authenticates users to your app.
- Test Lab: Firebase provides a real, cloud-based app testing infrastructure feature. Testing your application physically on each mobile device is often a burdensome activity. Test Lab lets you test your application with a variety of devices. It also provides a robo-test feature that will automate your app testing. In addition to testing, it gives a detailed analysis report for each device you choose during the test. Test Lab gives you a better insight into how your app will perform in real time.
- Hosting: Firebase provides a secure connection to serve your content with its hosting services. It offers fast and secure hosting for dynamic static content, microservices, and web applications. Firebase hosting also facilitates SSL certificates for your domain to ensure that your data is served securely.
MongoDB is an open-source NoSQL, dynamic-based, document-oriented database management system (DBMS). In terms of storing data, MongoDB differs from traditional databases. It stores the data in a collection of documents. The document represents data in JSON-like format, offering flexibility and high-speed data retrieval.
MongoDB is highly reliable and efficient because of its scaling, file storage, load balancing, aggregation, and other capabilities. These features enable MongoDB to fulfill high-speed and storage requirements.
MongoDB is compatible with various languages, including Python, C, C++, Java, Go, Node.js, and PHP. And it supports operating systems like macOS, Windows, and Linux.
Following are the key features of MongoDB that make it unique.
- Sharding: MongoDB supports sharding through horizontal scaling for better data distribution and storage. Sharding is a process of distributing your data across multiple servers, shards, or collections. MongoDB allows you to add additional servers to your database to obtain scalability and high performance with sharding. Each shard works as an independent database, and together they make a single logical database.
For instance, if a database has a 1TB data size and is distributed amongst two shards, then each shard will hold 512 GB of data. As a result, sharding also contributes to better load balancing. With sharding, you can also manage data load across multiple servers without any manual effort.
With increasing data size in organizations, it is essential for you to manage massive data growth. If you are depending on a single server, it will lead to improper read-write throughput, storage, and load-balancing issues.
- Replication: If data is stored in one place and exposed to vulnerabilities, it gets difficult to access and recover it. Replication ensures that your data is always available whenever required by deploying multiple servers for backup.
Replication is a process of a synchronizing set of copies/replicas so that changes made in one copy reflect in all other copies. This process creates multiple copies of your database, enhancing redundancy and superior data availability.
Similar to sharding, replication also helps in load balancing. When multiple users access the same data, it evenly distributes the load on different servers, enhancing the data availability without latency.
- Indexing: Indexing is a way of organizing data in a database so that it can return relevant results. If done right, this feature helps improve searching speed and overall performance of the database. However, if there are no indices, the database will scan through the entire collection of documents to match the query. This could be a time-consuming and resource-intensive process.
MongoDB overcomes this limitation with the indexing feature. Searching is efficient with MongoDB if you provide the correct index on your document, even if it has a large number of records.
- Aggregation: Using the aggregation function, you can process multiple documents to achieve computed results. Aggregation functions in MongoDB are used to group values from multi-document and perform functions on grouped data.
Firebase & MongoDB: Similarities
In order to understand the differences between both services, let’s start with what they have in common.
As Firebase and MongoDB are NoSQL databases, both have flexible data structures. Unlike relational databases, which have fixed schema and tables, NoSQL databases store data in JSON-like format. This offers high scalability and availability of voluminous data.
Properly distributing hundreds of client requests to multiple servers defines the ability of a database to handle the workload. With sharding features, the load on the server is effortlessly balanced, eliminating latency and performance issues. Both Firebase and MongoDB offer high scalability with their sharding feature.
Both MongoDB and Firebase are designed to provide optimal security at scale. Firebase follows its security protocols to protect your data in cloud storage, real-time, or Cloud Firestore databases.
MongoDB also offers some best key security features that include authentication, authorization, encryption, and TLS/SSL. Users in MongoDB are authorized with role-based access control (RBAC). It grants users access to perform only specific actions on resources.
Firebase Vs. MongoDB: Differences
Even if both provide various similar features, they differ in some aspects. Let us understand how they differ from each other through this section.
Firebase Vs. MongoDB: Performance
Firebase and MongoDB databases are designed to perform well. However, Firebase performs well in handling real-time data for mobile applications. With Firebase’s Realtime Database, you can get low latency in offline mode. But, it can impact application performance as all the data is stored together in a single object. To overcome this, you need to store data in Cloud Firestore because it stores your data across multiple data centers in distinct regions.
MongoDB provides superior performance for web-based applications. It also offers the strong querying capability to handle voluminous data both on-premises and on the cloud. It is designed to provide high performance for high-traffic web applications.
Firebase Vs. MongoDB: Use Cases
When choosing a database for large-scale applications that require complex querying and analysis, MongoDB is the best fit for your applications. MongoDB can be used if your application requires complete configuration management, real-time analytics, high-speed logging, and high scalability.
On the other hand, if you are developing a mobile application that needs real-time synchronization and supports offline mode, Firebase is the optimal solution. It can support chat applications, gaming apps, social network apps, or real-time collaboration tools.
Firebase Vs. MongoDB: Cost
Firebase offers two plans: Spark Plan (no-cost model) and Blaze Plan (pay-as-you-go). The no-cost model offers services that you can use free of charge, such as in-app messaging, cloud messaging, A/B testing, application delivery, etc. In the Blaze plan, you can pay as much as you use.
MongoDB is open-source, so you can also download and run it on your local machine. It is completely free if you want to use it on your organization’s servers. But if you need high levels of use, then it has MongoDB Atlas, a paid solution.
Choosing the correct database definitely depends on the requirements list and the environment you want to work in.
Firebase is optimal for application development. As it is a Backend-as-Service, it includes several services to boost your mobile application, like hosting, offline storage, and cloud storage. On the other hand, MongoDB is the best fit if your project holds massive amounts of data.