The task began with understanding the core requirements: a flexible schema to handle diverse data types like user profiles, posts, media, comments, likes, and notifications. NoSQL databases like MongoDB are ideal for such use cases because of their schema-less nature, which allows for scalability and adaptability as the app evolves.
Designing the schema required balancing normalization and denormalization. For example, embedding media metadata directly within posts simplified queries but required careful handling of updates. Similarly, caching counts like likes_count and comments_count in the Posts collection improved read performance at the cost of eventual consistency.
Creating the API endpoints was about ensuring usability and efficiency. Each endpoint was designed to handle specific user actions, from registering and logging in to uploading media and interacting with posts. The goal was to make the API intuitive for developers while optimizing for performance, especially with media-heavy operations.
One of the most interesting aspects was accommodating media content like images, videos, and GIFs. This required thoughtful schema design to store metadata (e.g., dimensions, duration) and efficient handling of media uploads and delivery via CDNs.
Overall, this assignment highlighted the importance of flexibility, scalability, and performance in modern app development. It reinforced the idea that a well-designed schema and API are the backbone of any successful social media platform, enabling seamless user experiences and future growth.
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