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BookHaven — System Design & Architecture Exploration

BookHaven is an online bookstore implemented using multiple backend architectures to explore system design tradeoffs, data modeling decisions, scalability, and developer experience.

This repository serves as the central index and comparison hub for all implementations.

The intent is not feature duplication — it is architectural comparison.


Why Multiple Implementations?

The same problem domain (online bookstore) was implemented using different stacks to study:

  • Relational vs NoSQL data modeling
  • Backend scalability vs data integrity
  • Development speed vs strict schema control
  • System complexity vs maintainability

Each implementation emphasizes a different engineering concern.


Implementations

1️⃣ Node.js + Express + MongoDB (Flagship)

🔗 https://github.com/JivaniParth/online-book-store-mongodb

Primary focus

  • REST API design
  • JWT authentication
  • Scalable NoSQL schemas
  • Admin + customer workflows

This is the most complete and demo-ready system.


2️⃣ Flask + MySQL

🔗 https://github.com/JivaniParth/online-book-store

Primary focus

  • Relational schema design
  • SQL joins and constraints
  • Transactional consistency
  • Backend clarity over flexibility

3️⃣ Recommendation Engine (Experimental)

🔗 https://github.com/JivaniParth/Recommandation-Model-for-online-bookstore

Primary focus

  • Recommendation logic
  • Data flow experimentation
  • Service separation
  • A/B testing foundations

This is a supporting system, not a full product.


Architecture Comparison

Aspect Node + MongoDB Flask + MySQL Recommendation Engine
Core Goal Scalability & UX Data Integrity Personalization
Data Model NoSQL Relational Hybrid
Flexibility High Low Medium
Complexity Medium Medium High
Production Readiness High High Partial

Key Takeaways

  • No architecture is universally correct
  • Tradeoffs must be explicit
  • Documentation is part of engineering
  • Clear intent matters more than tool count

Future Work

  • Integrate recommendation engine into flagship app
  • Add performance benchmarks
  • Introduce caching and async processing

Author: Parth Jivani

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