Denormalized Schema
A denormalized schema is a database design approach where data is intentionally duplicated across tables to optimize read performance and simplify queries, often at the expense of increased storage and potential data inconsistency. It reduces the need for complex joins by storing related data together, making it faster to retrieve information in read-heavy applications. This contrasts with normalized schemas, which minimize redundancy to ensure data integrity and reduce update anomalies.
Developers should use denormalized schemas in scenarios where read performance is critical, such as in data warehousing, analytics platforms, or high-traffic web applications where queries need to be fast and simple. It is particularly useful for reporting systems, caching layers, or NoSQL databases like MongoDB, where denormalization is a common practice to handle large-scale data retrieval efficiently. However, it requires careful management of data updates to avoid inconsistencies.