"A native multi-model database from the ground up, supporting key/value, document and graph models. You can model your data in a very flexible way."
Which actually seems like it could actually justify having its own query language. The built in search is also a nice touch.
You get 1000+ results.
So you filter by avg.star-rating > 4.0
Still 500+ results.
Those with just one 5 star rating in front of the one with 300 reviews and a 4.8 avg. Annoying.
What I really want:
I would like to filter for products that have at least 5 (relatively long) reviews, an average rating of 4.0 and at least 2 of these review comments mentioning the use case for which I would like to use this product. Maybe I just want the verified purchases to be counted or the reviews of friends and friends of friends...
Using a native multi-model approach you can do both. Simply retrieve all category X products ranked by product rating, limit 50/page or perform advanced lookups - without having to synchronize data from a document or relational model with an additional graph or search engine.
Combining full text search with scorers, graph traversals and/or join operations you could do an ad-hoc query in AQL to get the most relevant products & reviews with a single query.
Multi-model provides choice. In data modeling and querying.
That's easy enough to solve with a bayesian average. The problem is many developers and product managers don't know much or anything about stats.