What kind of workloads are materialized views designed to speed up?

• A. Workloads composed of common, repeated query patterns
• B. Highly unique ad-hoc queries
• C. Small data volumes
• D. Write-heavy transactional workloads

Answer: (A)

Materialized views speed up workloads by precomputing and storing the results of a query so that repeated executions of the same pattern can be answered quickly without reprocessing the entire dataset. This is especially beneficial when you have common, repeated query patterns—such as the same aggregations or joins over large tables that populate dashboards or BI reports—because the system can return the precomputed results instead of running the heavy query again.

As data changes, the materialized view is refreshed to keep results up to date, which introduces some maintenance overhead. That overhead is worthwhile when the same queries are run often, but it makes materialized views less desirable for highly unique, ad-hoc queries or for write-heavy transactional workloads where the cost of keeping the view updated can outweigh the performance gains. For small data volumes, the benefits are also typically minimal.