Welcome to another crucial lesson on your journey through network and data management. Today’s focus is understanding the key differences between relational and non-relational databases—an essential topic for technical interviews.

In interviews, you might encounter questions such as:

• "What are the key differences between relational and non-relational databases?"
• "Can you explain scenarios where you would choose a non-relational database over a relational one?"
• "How do data models differ between relational and non-relational databases?"

These questions aim to evaluate your understanding of different database architectures, data modeling, and your ability to choose the appropriate database type based on application needs.

Relational Databases (RDBMS)

• Structure: Use tables with rows and columns, ideal for structured data.
• ACID Properties: Ensure atomicity (all-or-nothing transactions), consistency (valid state transitions), isolation (independent transactions), and durability (permanent results), making them reliable for transactions.
• SQL: Utilize Structured Query Language (SQL) for defining and manipulating data.

Non-Relational Databases (NoSQL)

• Variety of Models: Include document, key-value, column-family, and graph databases, offering flexibility for different data types.
• Schema-less: Often don’t require a fixed schema, making them well-suited for unstructured or semi-structured data.
• Scalability: Designed for horizontal scalability, suitable for large-scale applications.

Understanding these differences will help you determine which type of database is best suited for different scenarios.

Why It Matters

• Performance & Scalability: Choosing the wrong database type can impact system performance and scalability.
• Data Integrity: Ensuring data integrity and reliability is vital, especially in transactional systems.