User behavior can be represented as a semantic vector in a similar way as text or images. Vector database allows you to create a real-time recommendation engine. No MapReduce cluster required.
Matching semantically complex objects is a special case of search. Usually a large number of additional conditions are used in matching, which makes Qdrant an ideal tool for building such systems.