How do you denormalize a database?

Denormalizing a database involves intentionally introducing redundancy or combining tables to optimize read performance and simplify query complexity. This is done after a database has been normalized (structured to minimize data duplication) but requires adjustments to address specific performance bottlenecks. The goal is to reduce the number of joins needed for common queries, which can improve response times in read-heavy applications. Common techniques include adding redundant columns, precomputing aggregated values, flattening related tables into a single structure, or using materialized views.

For example, consider an e-commerce database with normalized tables for orders, order_items, and products. A query to display an order summary (product names, quantities, and prices) would require joining all three tables. To denormalize, you might add a product_name column directly to the order_items table, eliminating the need to join with products for basic display purposes. Similarly, storing a total_price column in the orders table (precalculated from order_items) avoids recalculating sums during frequent reads. Another approach is merging tables with one-to-one relationships, such as combining user_profiles and user_settings into a single users table if they’re often accessed together.

However, denormalization introduces trade-offs. Redundant data increases storage costs and complicates updates—for instance, changing a product’s name would require updating all related order_items records. To mitigate inconsistency risks, use database triggers or application logic to synchronize duplicated values during writes. Denormalization is most effective when applied selectively to high-impact queries, such as dashboards or frequently accessed API endpoints. Start with a normalized schema, identify performance-critical read operations through profiling, then denormalize only the necessary components. This balanced approach maintains data integrity while addressing specific performance needs without overcomplicating the entire structure.