They do, but joins still cause unpredictable data scan jumps. Even if perfectly optimized. Think of an analytic query over a star schema, maybe the query needs

They do, but joins still cause unpredictable data scan jumps. Even if perfectly optimized. Think of an analytic query over a star schema, maybe the query needs 10 or 20 joins to align all the data for each of the fact tables, and scans most of the data (some aggregate report over the last year of data), but these joins don't reduce the cardinality much. If you look at the data access pattern, it's scattered all over the place for each joined row. You end up needing to read in a lot of data, possibly many times to complete the query.