It seems like I run into lots of situations where the appropriate way to build my data is to split it into two documents. Let's say it was for a chain of stores and you were saving which stores each customer had visited. Stores and Customers need to be independent pieces of data because they interact with plenty of other things, but we do need to relate them.
So the easy answer is to store the user's Id in the store document, or the store's Id in the user's document. Often times though, you want to access 1-2 other pieces of data for display purposes because Id's aren't useful. Like maybe the customer name, or the store name.
Would appreciate your input and/or links to any kind of 'best practices' or at least well-reasoned discussion of these topics.
There are basically two scenario's: fresh and stale.
Storing duplicate data is easy. Maintaining the duplicate data is the hard part. So the easiest thing to do is to avoid maintenance, by simply not storing any duplicate data to begin with. This is mainly useful if you need fresh data. Only store the references, and query the collections when you need to retrieve information.
In this scenario, you'll have some overhead due to the extra queries. The alternative is to track all locations of duplicate data, and update all instances on each update. This also involves overhead, especially in N-to-M relations like the one you mentioned. So either way, you will have some overhead, if you require fresh data. You can't have the best of both worlds.
If you can afford to have stale data, things get a lot easier. To avoid query overhead, you can store duplicate data. To avoid having to maintain duplicate data, you're not going to store duplicate data. At least not actively.
In this scenario you'll also want to store only the references between documents. Then use a periodic map-reduce job to generate the duplicate data. You can then query the single map-reduce result, rather than separate collections. This way you avoid the query overhead, but you also don't have to hunt down data changes.
Only store references to other documents. If you can afford stale data, use periodic map-reduce jobs to generate duplicate data. Avoid maintaining duplicate data; it's complex and error-prone.