PostgreSQL 19 introduces a significant optimization for data aggregation, allowing the optimizer to choose between aggregating first and joining later, or vice versa. This seemingly small tweak has major performance implications. In traditional queries, the process often requires multiple lookups for each product, slowing down operations. The new method changes this by allowing aggregation to occur earlier in the process, significantly reducing the amount of data that needs to be handled in subsequent joins. The article presents two query plans to illustrate the difference in performance. The first plan shows a costly sequence of scans and joins, resulting in a high total cost of about 13,170. In contrast, the optimized plan has a total cost of only around 4,638, showcasing a drastic reduction in the number of operations and data processed. This efficiency gains come from aggregating by `color_id` first, which limits the data that needs to be joined later. Despite these advancements, there are limitations, particularly with the CUBE functionality, which may not benefit as much from the new aggregation strategy. Nonetheless, these updates promise to enhance performance significantly for many users without requiring any changes to existing code or parameters. Overall, PostgreSQL 19's enhancements represent a major step forward in database efficiency.