Denormalization vs Materialized Views

Developers should use denormalization when dealing with read-heavy applications, such as analytics dashboards, reporting tools, or e-commerce platforms, where fast data retrieval is critical and write operations are less frequent meets developers should use materialized views when dealing with slow, complex queries in read-heavy applications, such as reporting dashboards, data analytics, or caching frequently accessed data. Here's our take.

Denormalization

Nice Pick

Developers should use denormalization when dealing with read-heavy applications, such as analytics dashboards, reporting tools, or e-commerce platforms, where fast data retrieval is critical and write operations are less frequent

Pros

• It is particularly useful in scenarios where complex joins slow down performance, as it simplifies queries by pre-combining related data into a single table
• Related to: database-normalization, sql-optimization

Cons

• Specific tradeoffs depend on your use case

Materialized Views

Developers should use materialized views when dealing with slow, complex queries in read-heavy applications, such as reporting dashboards, data analytics, or caching frequently accessed data

Pros

• They are ideal for scenarios where real-time data is not critical, as they reduce database load and latency by serving precomputed results
• Related to: postgresql, oracle-database

Cons

• Specific tradeoffs depend on your use case

The Verdict

These tools serve different purposes. Denormalization is a concept while Materialized Views is a database. We picked Denormalization based on overall popularity, but your choice depends on what you're building.

The Bottom Line

Denormalization wins

Based on overall popularity. Denormalization is more widely used, but Materialized Views excels in its own space.