SQL (Structured Query Language) and NoSQL (Not Only SQL) are two major types of databases, each designed for different use cases. Here’s a breakdown of their key differences:
| Feature | SQL Databases | NoSQL Databases |
|---|---|---|
| Structure | Relational (Tables with rows & columns) | Non-relational (Document, Key-Value, Column-family, Graph) |
| Schema | Fixed schema with predefined structure | Flexible schema, dynamic fields |
| Scalability | Vertical scaling (adding more power to a single server) | Horizontal scaling (distributing data across multiple servers) |
| Transactions | Supports ACID (Atomicity, Consistency, Isolation, Durability) | Supports BASE (Basically Available, Soft state, Eventually consistent) |
| Query Language | Uses SQL (Structured Query Language) | Varies; Uses JSON, key-value, graph queries, etc. |
| Best For | Structured data, complex queries, consistency (e.g., financial systems, ERP, CRM) | Unstructured/semi-structured data, fast read/write, scalability (e.g., real-time analytics, social media, IoT) |
| Examples | MySQL, PostgreSQL, SQL Server, Oracle | MongoDB, Cassandra, Redis, DynamoDB, Neo4j |
When to Use SQL vs. NoSQL
- Choose SQL if data integrity and consistency are critical (e.g., banking, accounting).
- Choose NoSQL if scalability, flexibility, and speed are priorities (e.g., social media, big data applications).
If you want to Learn SQL we have full playlist of MySQL and PostgreSQL Tutorials, for NoSQL we have playlist of MondoDB on our channel.