Implementing materialized views is recognized for improving performance in complex queries because they are pre-computed data sets that store the results of a query physically. This approach allows for quicker access to data by storing aggregate results or joining tables, which reduces the need to execute complex queries repeatedly on large data sets. As a result, when the materialized view is queried, the system can return results much faster, significantly enhancing performance, especially in scenarios where the underlying data does not change frequently and the same complex queries are run often.
In contrast, while normalizing a database can enhance data integrity and minimize redundancy, it typically involves more complex queries when retrieving data, which could lead to performance degradation rather than improvement. Using stored procedures can offer advantages such as code reusability and the encapsulation of business logic, but they do not inherently enhance query performance unless they are specifically optimized for performance. Increasing server resources can enhance performance to some extent but does not directly address the efficiency of query execution across complex queries as effectively as materialized views do.