This content originally appeared on DEV Community and was authored by Anjali Gurjar
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.
This content originally appeared on DEV Community and was authored by Anjali Gurjar
Anjali Gurjar | Sciencx (2025-02-01T05:03:04+00:00) SQL vs. MongoDB. Retrieved from https://www.scien.cx/2025/02/01/sql-vs-mongodb/
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