Normalization optimises for clean writes; denormalization optimises for fast reads. Production apps lean normalized, analytics systems often denormalize deliberately — knowing when to do which is a mark of database maturity.
Key Points
- Normalized: no redundancy, consistent updates, more joins per query
- Denormalized: duplicated data, fewer joins, faster reporting reads
- OLTP transaction systems → normalize; OLAP/reporting → denormalize selectively
- Star schemas in analytics are structured denormalization (facts + dimensions)
- Summary tables are a safe denormalization: derived, rebuildable
- Denormalize only with a plan to keep copies in sync (jobs, triggers)