What is the difference between database optimization and query optimization?

Database optimization is broader. It covers queries, indexes, schema design, caching, connection handling, storage, and monitoring. Query optimization focuses only on improving how individual queries are written and executed.

When should you use indexing vs partitioning?

Indexing works best when queries need to find specific rows faster. Partitioning is useful when tables are very large and queries usually target a predictable slice of data, such as date, tenant, or region.

How do you know if a database query is slow because of missing indexes?

Check the execution plan using EXPLAIN or EXPLAIN ANALYZE. If the database performs a full table scan on a large table for a selective query, a missing or poor index is likely part of the issue.

Does database optimization reduce cloud costs?

Yes. Better queries, indexes, caching, and storage design reduce CPU, memory, I/O, and unnecessary scaling. That helps teams avoid over-provisioning cloud database resources.

When does caching help database performance?

Caching helps when the same data is read often and does not change constantly. It works well for expensive aggregations, reference data, session data, permissions, and dashboard metrics.

How do you optimize a database without breaking production?

Start with measurement, test changes on production-like data, and apply fixes gradually. Review execution plans, add indexes carefully, monitor latency and error rates, and roll back quickly if performance worsens.