A customer has asked that you improve performance for a small table with frequent read accesses. What buffering type do you recommend?

In this scenario, recommending full table buffering is ideal for improving performance on a small table that experiences frequent read accesses. Full table buffering allows all records of the table to be cached in memory. Consequently, when users perform read operations, the system can access the data directly from memory rather than fetching it from the database each time. This leads to significantly faster response times for read operations since memory access is much quicker than disk access.

Additionally, using full table buffering is particularly effective for small tables because it is manageable to keep the entire dataset in memory without significant resource overhead. Since the table is small and frequently accessed, the advantages of quick read access and reduced database load make full table buffering a suitable choice.

Other buffering types could be less effective in this context. For example, single record buffering allows access to individual records without caching the entire table, which may not optimize performance as effectively for frequent reads. Primary key buffering also focuses on specific entries based on their keys but doesn’t take advantage of the entire dataset being in memory. Column store is an entirely different approach, generally used for analytical queries rather than optimizing read access patterns on transactional tables. Therefore, full table buffering stands out as the most beneficial option for improving performance in this scenario.