You are designing a system for an e-commerce platform. A 'Product' has 50 attributes, but only 5 are used for the search results page. The 'Reviews' can grow into the thousands. How do you model this?

For the search results page, having a dedicated search collection with only the necessary fields provides dramatic performance benefits. Queries can use a compound index on category, price, and brand to return results quickly. MongoDB can even cover the query entirely from the index if all returned fields are in the index, eliminating document fetches. This approach is superior to trying to optimize queries against the full product collection, where 45 unnecessary fields would be loaded into memory for every search result.

Storing reviews separately solves multiple problems. First, it eliminates the 16MB limit concern—products can have unlimited reviews. Second, it enables efficient pagination: you can fetch 10 reviews at a time with skip() and limit(). Third, you can create separate indexes for different review queries, like finding all reviews by a user or calculating average ratings. The trade-off is that retrieving a product with its reviews requires either two queries or a $lookup aggregation, but the performance benefits of keeping reviews separate far outweigh this cost.