SQL vs. MongoDB

Advantages of MongoDB (NoSQL)
✅ Schema-less → No need to predefine structure, store flexible data.
✅ Fast Writes & Reads → Optimized for large-scale unstructured data.
✅ Horizontal Scaling → Supports sharding for distributing data across multiple servers.
✅ Better for Real-Time Apps → Chat apps, IoT, logs, analytics.

When to Use SQL vs. MongoDB
Use Case Recommended Database
E-commerce (Orders, Payments) ✅ SQL (Transactions, ACID compliance)
Real-Time Chat (Messages, Notifications) ✅ MongoDB (Fast inserts, flexible schema)
Banking & Financial Apps ✅ SQL (Strong consistency, security)
Social Media (User Profiles, Posts) ✅ MongoDB (Scalable, high read/write)
Analytics & Logs ✅ MongoDB (Fast insertions, unstructured data)
Inventory Management ✅ SQL (Relational data, constraints)

Aspect SQL (Sequelize) NoSQL (MongoDB Mongoose)
Schema Fixed schema Dynamic schema
Query Language SQL JSON-like queries
Joins Supports joins (INNER JOIN, LEFT JOIN) Uses embedding instead of joins
Scalability Vertical scaling Horizontal scaling
Transactions ACID-compliant Limited transaction support
Performance Better for complex queries

Requirement Best Choice
Structured Data, Relationships, Transactions SQL (PostgreSQL, MySQL with Sequelize)
Unstructured Data, Scalability, Fast Reads/Writes MongoDB (Mongoose, Native Driver)
🔹 Use SQL if your data is highly relational (e.g., banking, orders).
🔹 Use MongoDB for flexible schemas, real-time updates, and big data applications.