How can Firestore be used to build a scalable feed and follow system for social networks?

Addressing Scalability Issues with Feed and Follow Systems in Firestore

In the world of social networking, creating a scalable feed and follow system is crucial to ensure optimal performance and user experience. When using Firebase Realtime Database, the limitations of large user followings and the retrieval of all posts for new followers posed significant challenges. Firestore, on the other hand, offers a more scalable solution.

Proposed Firestore Database Structure

To address the scalability issues, we propose a schema that includes three top-level collections for:

• Users: Contains user information such as name and email.
• Following: Represents the users that a user is following. Each document under this collection has a collection called "userFollowing" that contains the uids of the followed users.
• Posts: Stores user posts. Each document under this collection has a collection called "userPosts" that contains the ids of the posts created by that user.

Eliminating Scaling Problems

Problem 1: A large number of posts being added to the timelines of followers

Solution: The use of collections allows Firestore to handle large amounts of data efficiently. Even if a user has a large number of followers, the addition of a new post only affects the respective user's "userPosts" collection. No additional data is copied across the database.

Problem 2: New followers receiving all posts from users with numerous posts

Solution: Instead of storing all posts in one place, they are stored in each user's "userPosts" collection. This enables efficient query operations based on cursors and limits. As users scroll down their timelines, only the latest posts are retrieved in chunks.

Additional Optimization

May 20, 2019 Update: To further optimize performance, it's beneficial to create a document for each user's feed. This document can store the recent posts of the users they follow. This approach minimizes the need to query multiple collections and allows for faster loading of user timelines.

Benefits of This Structure

• Efficient handling of large followings and large amounts of posts
• Fast and scalable query operations
• Reduced data duplication and improved storage efficiency
• Enhanced user experience with optimized timeline performance

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