The standard pattern to avoid select for update (which can cause poor performance under load) is to use optimistic concurrency control.

Add a numeric version column to the table being updated, read and increment it in the application layer and use the value you saw as part of the where clause in the update statement. If you see ‘0 rows updated’ it means you were beaten in a race and should replay the operation.

I don't think such a broad recommendation will be good for most people, it really depends.

Optimistic updates looks great when there is no contention, and they will beat locking in a toy benchmark, but if you're not very careful they can cause insane amplification under load.

It's a similar trap as spinlocks. People keep re-discovering this great performance hack that avoids the slow locks in the standard. And some day the system has a spike that creates contention, and now you have 25 instances with 24 of them spinning like crazy, slowing to a crawl the only one that could be making progress.

It's possible to implement this pattern correctly, and it can be better in some specific situations. But a standard FOR UPDATE lock will beat the average badly implemented retry loop nine times out of ten.

Good point. The barrier pattern from the article applies to both approaches - whether you're using pessimistic locks or optimistic version checks, it's good to verify that the concurrency handling actually works. Barriers let you test that your version check correctly rejects the stale update, the same way they test that your lock prevents the race.