Firebase Vs Firestore - Which is More Reliable for Real-Time Applications?

When building a modern application, selecting the right tools becomes substantially important. Backend services are responsible for tasks like processing front-end-request and handling data traffic. At the same time, database is a key component of backend service that handles the storage and management of data.

Google offers Firebase and Firestore, two robust tools that help optimize the application development process. While Firebase is a Google service platform that supports many backend services, including a database, Firestore is a scalable NoSQL database offered by Firebase.

This article will outline the comparative Firebase vs Firestore features, helping you choose the best solution. 

Firebase: More than a Database

Firebase is an application development platform. It offers a fully managed infrastructure and a variety of services such as app hosting, cloud storage, Firebase ML, realtime database, and more. These services help you store and sync your application data, improve scalability, and provide backend support. It also facilitates cross-platform application development SDKs that help you build and ship apps to iOS, Android, and the Web.

Key Features of Firebase

• Application Hosting: Firebase’s App Hosting is a full-stack solution. It helps you manage both client-side rendering and server-side rendering. You can easily and quickly launch your application without having to set up any complex infrastructure. ‍
• Robust Security: Firebase provides ingrained privacy for your application through App Checks and authentication. App Check enables you to protect the backend resources by attesting incoming traffic and end-to-end identity solutions for email, password accounts, and login authentication.‍
• Realtime Database: The Firebase Realtime Database is cloud-hosted and stores data as JSON. When you build a cross-platform app with Firebase SDKs, all the clients share a Realtime Database instance, which automatically receives updates with the newest data.
• ‍Crashlytics: The Crashlytics service helps you track and fix errors in your application. It captures crashes and groups them into manageable issues, prioritizing these crashes based on their impact on the user.
• ‍Firebase ML: You can leverage Firebase ML to train and deploy custom models over the air. The Firebase ML kit is a mobile SDK that brings Google ML expertise to Android and Apple apps where you can implement the functionality you need with just a few lines of code.

Firestore: A NoSQL Database 

Firestore is a NoSQL Google Firebase database. You can use Firestore to build scalable web and mobile apps, and server-side applications with ease. As a document-based database, the data within this db instance is stored in a hierarchical collection of documents. Firestore also facilitates offline support, enabling your application to function without an internet connection. These diverse features make Firestore ideal for a variety of use cases, such as up-to-date synchronization and managing complex data structures.

Key Features of Firestore 

• Flexibility: Firestore uses a document-oriented data model. You can store your data in the form of documents. These documents are flexible and support complex and hierarchical data structures, such as arrays and nested objects. 
• ‍Expressive Querying: In Firestore, you can use queries to retrieve either a single document or all documents within a collection. The queries can be simple or compound and can include multiple operations such as filtering and sorting. 
• ‍Offline Support: Firestore provides offline support by caching your application data locally. This allows you to query the data even when the device is offline. Once the device comes back online, Firestore synchronizes all the changes to the cloud.
• ‍Scalability: The auto-scaling in Firestore allows you to handle growing data traffic and intensive workloads without any difficulty or maintenance. Firestore automatically adjusts the resources to accommodate your application demand, ensuring consistent performance.
• ‍GenAI Integration: You can build GenAI applications by integrating Firestore with libraries like LangChain and LamaIndex. The integration enables you to load and store documents using a Document loader, Vector Store, and Memory.

Firebase Vs Firestore: Key Differences

The main difference between Firebase and Firestore is that Firebase is a comprehensive app development platform offering real-time databases, authentication, and hosting, while Firestore is a NoSQL database within Firebase, optimized for real-time data synchronization and scalability.

The table below highlights how Firebase and Firestore have differing data modeling, querying, and scaling capabilities:

Here is a detailed explanation of Firebase vs Firestore comparative features:

Service Type

Firebase offers you a comprehensive set of tools and services for building and running applications. These services include app hosting, cloud functions, Genkits, app distribution, remote configuration, and more. You can also use the Firebase Realtime database to store data, which is suitable for small-scale applications.

Whereas, Firestore is a NoSQL database that is a part of the Firebase product spectrum. You can utilize Firestore to store, query, and synchronize data for web and mobile applications. Firestore focuses more on scalability, flexibility, and data management, making it suitable for large-scale applications.

Data Modeling 

In Firebase Realtime Database, you can store data in a single large JSON tree, where all of your data is represented in a hierarchical structure. However, as the data grows and becomes more complex, querying and organizing data becomes a bit challenging.

In contrast, Firestore provides a more flexible data model. It uses a collection of documents to store the data. These documents are very similar to JSON objects. Each document contains a key-value pair and is grouped together within a collection, making it easy to query, manage, and scale data.

Scalability 

You can use the Realtime Firebase database to scale around 200,000 concurrent connections and 1000 writes per second. To scale beyond this limit, you can split your resources among multiple real-time database instances to balance the load. 

Firestore is comparatively more scalable than Firebase. It provides automatic scaling. You can use Firestore to scale up to one million concurrent connections and 10 thousand writes per second. 

Reliability and Performance 

Firebase provides low latency, lower than Firestore, with 10 ms for response and real-time updates. These features make it ideal for applications that require instant data synchronization among multiple devices. 

In comparison to Firebase, Firestore is a more robust solution when it comes to reliability and performance. It supports multi-region replication, ensuring high data availability, and can handle large and complex datasets more efficiently than Firebase. 

Security  

Firebase supports GDPR and CCPA to protect personal and business data. It facilitates App Check for data integrity and validation and Firebase Authentication to prevent unauthorized access. Other than this, Firebase monitoring allows you to calculate the number of unique Firebase installations that access resources to inspect access patterns.

Firestore, on the other hand, provides security through features like IAM, server-side encryption, Firebase security rules, and configuration language. You can implement security rules for access control and data validation. These rules can be customized according to the data model you create. Besides this, the Firestore uses server-side encryption to automatically encrypt data before writing it to disk and decrypt it when read by an authorized user. 

Pricing and Cost Consideration: Firestore vs Firebase

Firestore and Firebase both offer you two types of pricing models. The Free-tier model enables you to start working with your database and application at no cost for a certain period of time. For the pay-as-you-go model Firebase and Firestore charge you based on the services you want to acquire and operations you want to perform.

When you are using Firestore pricing plan, you are charged for: 

• The number of documents you want to read, write or delete. 
• The number of index entries used to satisfy a query 
• The amount of storage your database uses. 
• The network bandwidth.

Other than these factors, the pricing also depends on the location where you deploy your database. 

In contrast to Firestore, Firebase’s pay-as-go model consists of services like: 

• App hosting, 
• Authentication,
• Cloud Functions, 
• Cloud Firestore, 
• Cloud Storage, 
• Test Lab, 
• Firebase ML and more.

Each of these services offers a subset of operations that you can perform and are charged for per second or per minute a day.

Choosing Between Firebase Vs Firestore Based on Use Cases 

Below are some use case scenarios that will help you examine which database, Firebase Realtime database or Firestore, best suits your application requirement.

Scenarios Favoring Firebase  

• Real-Time Data Synchronization: You can use Firebase Realtime Database in a live chat application for conversation synchronization, collaborative tools where multiple users work on the same data, or tracking services. 
• Simple Data Structure: Firebase can be optimized for applications with simple data structures that do not require complex queries like messaging apps or inventory systems. 

Scenarios Favoring Firestore  

• Complex Querying: Firestore can be optimized to perform advanced queries such as searching, filtering, or aggregation. These queries are useful for applications like e-commerce platforms or content management systems.
• Offline Support: Firestore offers a built-in offline support and synchronization service. It is helpful for applications that need to function without a constant internet connection.

Synchronizing Data in Firestore or Firebase Using Airbyte

Synchronizing data between Firestore and Firebase can be useful for a variety of reasons. For instance, the integration improves data consistency within the Google Cloud platform. However, synchronizing and mapping data correctly between these databases can be difficult due to the difference in how they organize and store data.

‍Airbyte is an automated data integration tool that helps you seamlessly migrate and synchronize data between different systems, including databases such as Firestore and Firebase. It offers a library of 400+ pre-built connectors. Using these connectors, you can build a data pipeline and migrate and map your data from source to destination with minimal coding. 

Let’s see how Airbyte simplifies data synchronization: 

• Change Data Capture: CDC allows you to identify the incremental changes made in your source database and replicate them in the destination. This helps you keep track of all the updates, maintaining data consistency.
• Flexible Customize Connectors: Airbyte offers different options to build custom connectors, including connector builder, low code connector development kit, Python CDK, and Java CDK. For instance, using these CDKs, you can build a custom connector to load data from Firebase to Firestore. 
• Schema Management: With Airbyte schema management, you can specify how it will handle schema changes for each connection. This minimizes errors and accurately synchronizes data between systems. Also, for users who utilize Airbyte Cloud, the tool checks the source data for change every 15 minutes. For a self-hosted environment, Airbyte runs checks immediately after syncing at most every 24 hours. 

Conclusion 

Firebase and Firestore are both powerful tools within Google’s ecosystem but serve different purposes. Firebase offers you a full-stack solution that simplifies application development with comprehensive backend services. Firestore, on the other hand, is a highly scalable NoSQL database that is used by 4.5% of developers to build applications that require handling large datasets and complex querying. When deciding between Firebase vs Firestore, it comes down to the specific needs of your application, including budget, scalability, and performance.