this post was submitted on 15 Jun 2023
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Ehhhhhhh. Using a relational database for Lemmy was certainly a choice, but I don't think it's necessarily a bad one.
Within Lemmy, by far the most expensive part of the database is going to be comment trees, and within the industry the consensus on the best database structure to represent these is... well, there isn't one. The efficiency of this depends way more on how you implement it within a given database model than on the database model itself. Comment trees are actually a pretty difficult problem; you'll notice a lot of platforms have limits on comment depth, and there's a reason for that. Getting just one level of replies to work efficiently can be tricky, regardless of the choice of DBMS.
Looking at the schema Lemmy uses, I see a couple opportunities to optimize it down the road. One of the first things I noticed is that comment replies don't seem to be directly related back to the top-level post, meaning you're restricted to a breadth-first search of the comment tree at serving time. Most comments will be at pretty shallow depths, so it sometimes makes sense to flatten the first few levels of this structure so you can get most relevant comments in a single query and rebuild the tree post-fetching. But this makes nomination (i.e. getting the "top 100" or whatever comments to show on your page) a lot more difficult, so it makes sense that it's currently written the way it is.
If it's true (as another commenter said) that there's no response caching for comment queries, that's a much bigger opportunity for optimization than anything else in the database.