Denormalization can improve performance from "summary" of SQL and Relational Theory by C. Date
Denormalization, as we've seen, involves deliberately violating the rules of normalization in order to achieve certain objectives. One of those objectives is often improved performance. But how can denormalization help in this way? The basic idea is this: If we denormalize, we reduce the number of joins that need to be performed, and joins are typically expensive operations in terms of time and resources. So, all other things being equal, if we denormalize, we may well speed up some queries. The key point here is that denormalization can be a trade-off. We sacrifice the benefits of normalization in order to achieve certain other objectives - such as improved performance. And, as always with trade-offs, we have to be careful. We have to weigh the advantages of denormalization against the disadvantages - and make sure we fully understand what we're doing. For example, when we denormalize, we introduce redundancy. And redundancy can cause problems. Specifically, it can lead to update anomalies, where inconsistencies can arise in the database. To avoid these anomalies, we may need to impose extra constraints on the data - which in turn can slow down update operations. So, we have to be careful - and remember, as always, that there's no free lunch. Furthermore, denormalization can also lead to data integrity issues. By duplicating data across multiple tables, we run the risk of inconsistencies creeping in. If a piece of duplicated data is updated in one place but not another, data integrity is compromised. This can be particularly problematic in systems where data accuracy is critical, such as financial or healthcare applications.- Denormalization can indeed improve performance by reducing the number of joins needed in queries. However, it comes with trade-offs such as increased redundancy, update anomalies, and data integrity issues. Therefore, it is essential to carefully consider the implications of denormalization and weigh the benefits against the drawbacks before implementing it in a database system.
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