You have to load every document in the database and extract the audit trail from it, then filter it in your app for the user you’re looking for. Just the though

You have to load every document in the database and extract the audit trail from it, then filter it in your app for the user you’re looking for. Just the thought of what that would do to my hardware was enough to turn me off the whole idea. Naive question from somebody who has done a little reading on and dabbling with key/document-with-MapReduce style datastores, but who hasn't tackled a real production problem: I thought running queries over the entire dataset was one of the assumptions of horizontally scalable document stores? In terms of avoiding computation, you can only limit queries by document key, which even if you're clever/lucky doesn't always encode the parameters you're querying on, or doesn't encode them in the right order, so you should be prepared to run queries over your entire dataset. Hopefully the queries you run often are optimized (e.g., using indexes or clever use of key ranges), but in the general case, you have to be prepared to scan the whole shebang, and that's supposed to be okay because of horizontal scalability, right?