System design interviews are no longer reserved for senior engineering roles—they're now a staple in tech interviews across the board. And if there’s one area that can either make or break your chances, it's how well you understand databases. Knowing which database to use and why can set you apart as a thoughtful, skilled engineer who understands trade-offs, scalability, and real-world architecture decisions.

In this article, I’ll walk you through 10 essential types of databases that every developer, especially those preparing for system design interviews, should know. These are not just definitions; these are insights that will help you speak the language of system design with confidence and clarity.

Bonus: If you’re looking for in-depth guides and coding resources, I’ve packed several in my latest ebooks available at codewithdhanian.gumroad.com. Check them out to deepen your understanding with real-world applications.

1. Relational Databases (SQL)

These are the classic workhorses of the database world. Think MySQL, PostgreSQL, and Oracle. They organize data into structured tables and use SQL for querying. They're ideal for systems where data integrity and relationships between entities are crucial—like banking systems, e-commerce, and CRMs.

When to mention it: "For strong ACID compliance and normalized data models, I'd choose a relational database like PostgreSQL."

2. NoSQL Databases

A broad category designed for flexibility and horizontal scaling. These databases are schema-less and include document, key-value, graph, and column-family databases.

Use them when your system needs to handle huge volumes of unstructured or semi-structured data, or when you need to iterate quickly without worrying about schemas.

3. Document Databases

Think MongoDB and CouchDB. These store data as JSON-like documents, making them perfect for content management systems, blogs, or user profiles.

System design insight: "I'd use a document database like MongoDB for storing user profiles where fields can vary greatly from one user to another."

4. Key-Value Stores

Blazing fast and extremely simple. Redis and DynamoDB are great examples. Perfect for caching, session stores, and real-time leaderboards.

Drop this line in your interview: "We can use Redis as a key-value store to cache frequently accessed user data and reduce read latency."

5. Wide-Column Stores

Popularized by Cassandra and HBase, these are perfect for systems that handle massive write loads and need fast querying across different columns. Great for IoT applications or recommendation engines.

6. Graph Databases

Neo4j is the go-to example here. These databases excel at handling complex relationships, like social networks or recommendation systems.

Tip: "A graph database would be ideal here to model and traverse relationships, such as user connections or interests."

7. Time-Series Databases

These are optimized for storing time-stamped data like logs, metrics, or sensor readings. InfluxDB and TimescaleDB are popular choices.

Used heavily in monitoring, analytics, and IoT.

8. Search Databases

Elasticsearch is the name to know. These databases are built for full-text search and are incredibly fast at indexing and querying massive datasets.

Perfect for log search, application search bars, and analytics dashboards.

9. NewSQL Databases

These aim to blend the best of SQL with the scalability of NoSQL. Google Spanner and CockroachDB are examples. They support ACID transactions and SQL querying but are built for distributed architectures.

Mention these when you want strong consistency at global scale.

10. Multi-Model Databases

Databases like ArangoDB and OrientDB combine multiple database models (e.g., document + graph + key-value) in one engine. They offer flexibility for applications that need to work with data in different formats without spinning up multiple database engines.

Conclusion

In system design interviews, it’s not about choosing the best database—it's about choosing the right one. Understand the trade-offs: consistency vs. availability, performance vs. flexibility, simplicity vs. power. If you can do that, you’re already ahead of most candidates.

And if you want a deeper breakdown of these database types with diagrams, sample architectures, and real-world examples, I’ve covered that in more depth in my ebook collections. Feel free to explore them at codewithdhanian.gumroad.com.

Take the time to learn these 10 database types—not just for the interview room, but for the real-world systems you’ll be designing and building.