One can't just say "joins are expensive on IO and transfer"; you have to specify exactly what kind of join you're talking about and how it's being used. The way an INNER JOIN will influences how rows are retrieved is completely different from how an OUTER JOIN or CROSS JOIN will.
In all those cases, the devil remains in the details. For example if you're just looking to add one or two columns to the result set, an INNER or OUTER JOIN usually reduces the amount of data that has to be shoved through the pipe. That's because you avoid transmitting the keys that are needed to join the data in-app. On the other hand, if you're joining a small number of larger values to a table with lots of rows, perhaps the join duplicates those values enough to really bulk up the result set. But it's effectively impossible to know whether that will be the case without measuring the performance for a couple different options.
Here's an alternative consideration: ORMs tend to encourage a style of coding wherein every column in the table is always grabbed all the time, regardless of how much of that information is actually needed for the task at hand. This is done in order to be able to generate full-fledged objects like the ORM wants to, and to reduce the amount of custom mapping that needs to be maintained. Now if you're looking for a needless waste of bandwidth, there's a needless waste of bandwidth.
If you're consistently having performance problems on joins, it's likely that the real culprit is poor configuration of keys and indexes. Or if you're not watching how the ORM chooses to join the data too closely, perhaps you've got some N+1 queries sneaking in there.
In all those cases, the devil remains in the details. For example if you're just looking to add one or two columns to the result set, an INNER or OUTER JOIN usually reduces the amount of data that has to be shoved through the pipe. That's because you avoid transmitting the keys that are needed to join the data in-app. On the other hand, if you're joining a small number of larger values to a table with lots of rows, perhaps the join duplicates those values enough to really bulk up the result set. But it's effectively impossible to know whether that will be the case without measuring the performance for a couple different options.
Here's an alternative consideration: ORMs tend to encourage a style of coding wherein every column in the table is always grabbed all the time, regardless of how much of that information is actually needed for the task at hand. This is done in order to be able to generate full-fledged objects like the ORM wants to, and to reduce the amount of custom mapping that needs to be maintained. Now if you're looking for a needless waste of bandwidth, there's a needless waste of bandwidth.
If you're consistently having performance problems on joins, it's likely that the real culprit is poor configuration of keys and indexes. Or if you're not watching how the ORM chooses to join the data too closely, perhaps you've got some N+1 queries sneaking in there.