MySQL doesn't support descending indexes, so for a large class of problems you will have to scan the entire index to find the last 10 items, especially when sorting by items in two directions. This is really slow when you have one hundred million entries (a huge events table). Looking up by primary key is very very fast in MySQL with InnoDB. If you profile this query you can see MySQL spends most of its time figuring out the IDs, and almost no time reading them back to you. Using Redis in this manner is very memory efficent, easy to update, and gets you 95%+ of the potential performance gains. It means we don't have to keep Redis up to date with edits or changes, because the PKs are set in stone.