What is the difference between normalization and denormalization?

Answer

Normalization organizes data to eliminate redundancy by splitting it into related tables, which reduces anomalies and keeps a single source of truth for each fact. Denormalization deliberately reintroduces redundancy, duplicating data across tables to avoid expensive joins and speed up reads. Normalized schemas favor write integrity and storage efficiency, while denormalized schemas favor read performance at the cost of more complex updates. OLTP systems lean toward normalization, whereas analytics and read-heavy systems often denormalize.