BookWorm.
BookWorm reimagines the digital reading experience by combining social discovery with editorial design principles.
Overview
BookWorm reimagines the digital reading experience by combining social discovery with editorial design principles. Built to help readers find their next favorite book through curated recommendations and community-driven reviews.
Core Pillars
Smart Recommendations
Personalized book suggestions based on reading history and community preferences.
Reading Lists
Create and share curated book collections with custom categories.
Social Reviews
Community-driven reviews with rich text formatting and threaded discussions.
API-First Architecture
RESTful API built with Node.js and SurrealDB for flexible data querying.
Graph-Based Recommendations
Traditional relational queries were too slow for generating recommendations across interconnected user preferences and book metadata.
The Solution
Leveraged SurrealDB's graph traversal capabilities to build a recommendation engine that queries relationships between users, books, and genres efficiently.
"Recommendation queries dropped from 800ms to under 50ms."
Real-Time Sync
Keeping reading progress synchronized across devices while handling offline scenarios gracefully.
The Solution
Implemented an event-sourcing pattern with conflict resolution, allowing seamless sync when connectivity is restored.
"Zero data loss across 10k+ sync events in testing."
Ready to explore the code?
BookWorm is open-source and available for review. Dive into the architectural decisions that power this project.