The resulting SQLite database file is currently 8.3 GB, most of which is taken up by the `links` table. The big performance wins are having a handful of indexes (see the .sql files[1] for the database's schema) and preprocessing a lot of data so I don't have to do duplicate work every time a query occurs. For example, instead of the `links` table going from `source_id` to `target_id` and having a ton of rows which have the same `source_id`, I go from `id` to `outgoing_links` (which is a |-separate string of all source page IDs). Computing each page's incoming and outgoing links is the really heavy work and I only do that at database creation time, using a beefy GCP machine with 8 vCPUs, 52 GB RAM, and a 256 GB SSD. It still takes about an hour, but it's a one time cost and means I can run the actual service on a much smaller machine which won't cost me a fortune to maintain. Also, SQLite is just very fast and performant out of the box, so as usual, it's a matter of choosing the right tools for the job.

[1] https://github.com/jwngr/sdow/tree/master/database