1.1 What is SQL?

SQL (Structured Query Language) databases are relational databases that store data in structured tables (rows and columns) with predefined schemas.

Examples:

• MySQL
• PostgreSQL
• Microsoft SQL Server

Key Characteristics

• Structured schema (schema-on-write)
• Supports JOIN operations
• Strong ACID compliance
• Best for structured and relational data

1.2 What is NoSQL?

NoSQL databases are non-relational databases designed for flexibility, scalability, and handling large volumes of distributed data.

Types

• Document (e.g., MongoDB)
• Key-Value (e.g., Redis)
• Column-Family (e.g., Cassandra)
• Managed NoSQL (e.g., DynamoDB)

Key Characteristics

• Flexible schema (schema-on-read)
• Horizontally scalable
• Optimized for large-scale distributed systems
• Often follow BASE consistency model

1.3 Core Differences

| Feature        | SQL                        | NoSQL                           |
|----------------|----------------------------|---------------------------------|
| Data Model     | Tables (Relational)        | Document / Key-Value / Column   |
| Schema         | Fixed, predefined          | Dynamic, flexible               |
| Scaling        | Vertical (scale-up)        | Horizontal (scale-out)          |
| Transactions   | Strong ACID                | BASE / Eventual consistency     |
| Relationships  | Strong (JOIN support)      | Typically denormalized          |

1.4 When to Use SQL

Use SQL when:

• You need complex queries and joins
• Strong data integrity is required
• The system is transactional
• Data structure is stable and well-defined

Examples

• Banking systems
• ERP systems
• E-commerce order management

1.5 When to Use NoSQL

Use NoSQL when:

• You need high scalability
• Data structure changes frequently
• Large volume of semi-structured/unstructured data
• Real-time or distributed systems

Examples

• Social media feeds
• Logging systems
• IoT platforms
• Caching layers