Which Database to choose?

Yesterday, during an interview, I was asked about the differences between MySQL, PostgreSQL, MongoDB, and DynamoDB. Honestly, I felt stuck. It's one thing to use databases in projects, but explaining their differences and use cases under pressure is another challenge altogether. So, I decided to dive deeper, and here’s what I learned:

1. MySQL
Type: Relational Database (SQL)
Best for: Structured data with defined schemas. Ideal for web apps with transactional operations, like e-commerce websites.

• Pros:
  Simple and easy to set up.
  Great for read-heavy workloads.
  Widely supported with robust community support.

• Cons:
  Not as flexible for complex queries as PostgreSQL.
  Limited scalability for massive datasets.
  Example Use Case: A blog platform where relationships between users, posts, and comments are predefined.

2. PostgreSQL
Type: Relational Database (SQL) with advanced features.
Best for: Complex data relationships, custom functions, and high scalability.

• Pros:
  Supports advanced queries, JSON storage, and geospatial data.
  Highly extensible with custom data types and indexes.
  ACID compliance ensures data integrity.

• Cons:
  Slightly steeper learning curve compared to MySQL.
  Example Use Case: A financial app requiring complex transactions and analytics.

3. MongoDB
Type: NoSQL (Document-based)
Best for: Unstructured or semi-structured data, rapid development, and flexible schemas.

• Pros:
  Stores data as JSON-like documents, making it flexible.
  Great for scaling horizontally.
  Ideal for real-time data apps.

• Cons:
  Doesn’t enforce relationships like relational databases.
  Can get expensive for massive datasets.
  Example Use Case: A social media app where user data is dynamic and doesn’t fit a strict schema.

4. DynamoDB
Type: NoSQL (Key-Value and Document-based) by AWS
Best for: Applications needing ultra-low latency and high scalability with minimal management.

• Pros:
  Fully managed by AWS, no server maintenance required.
  Built-in scalability for high read/write traffic.
  Great for event-driven apps.

• Cons:
  Limited querying capabilities compared to other databases.
  Vendor lock-in with AWS.
  Example Use Case: A serverless real-time leaderboard for a gaming app.

How I’d Answer Now
Choosing the right database depends on the application’s requirements:

Relational Databases (MySQL, PostgreSQL): Go for structured, consistent data. PostgreSQL is the winner for complex queries.
NoSQL Databases (MongoDB, DynamoDB): Perfect for flexible, schema-less data. DynamoDB shines for serverless, high-traffic applications, while MongoDB is excellent for rapid prototyping.
I’ve learned that being clear on use cases, strengths, and limitations is key in interviews. Next time, I’ll be ready—and I hope this helps you too!

Your Turn:
What’s your go-to database for your projects? Share your thoughts in the comments!