To expand: when you have to query a remote database for data, you likely only want to perform one query for performance reasons (and certainly not an unbounded amount of queries - maybe two or three is acceptable but not N+1). This means that information must be passed down the call stack for what information is needed in that single or few queries, creating coupling between unrelated layers of your application.

To make this more concrete: imagine you write a function to find users named Jim. At first this function is for reporting, so you just return a list of user IDs. Later, you decide to build a dashboard. You want to render all users named Jim here, but you need each of their names for display purposes.

Given a remote database, you now need to modify the query function to be able to return the specific attributes you need for this use case. You can imagine if you extend the call stack this passing gets more complicated, requires merging of the queried items, etc.

With datomic, since your data is in memory, your original query can stay the same, since N+1 queries are irrelevant when your data is available in RAM.

I think this point is important.

Also, I may not be getting what Datomic is, but why modify original function, you can just join results with users table.

In that scenario you could join the user table. You'd be overfetching in many scenarios but that's not a huge concern for most people, this is what active record does. However, say you want to get more than just the columns on the user table, then you run into the same issue. Suddenly the query caller needs to inform the query method to include results about some unrelated table. Because datomic is an in memory graph structure, the caller can handle grabbing that extra information without modifying the method or its call signature, obviating the need for this coupling.

http://www.dba-oracle.com/t_rman_149_flasbback_query.htm