rum

Thanks for following up :-) I was asking because ranking can be slow in PostgreSQL. PostgreSQL can use a GIN or GiST index for filtering, but not for ranking, because the index doesn't contain the positional information needed for ranking. This is not an issue when your query is highly selective and returns a low number of matching rows. But when the query returns a large number of matching rows, PostgreSQL has to fetch the ts_vector from heap for each matching row, and this can be really slow. People are working on this but it's not in PostgreSQL core yet: https://github.com/postgrespro/rum. This is why I'm a bit surprised by the numbers you shared: fulltext search on 270 million rows in below 65ms on commodity hardware (sub 8€/mo). A few questions, if I may: - What is the average number of rows returned by your queries? Is there a LIMIT

Used it for 10,000+ document and 1 million document projects. Was good enough for me (but I guess I wouldn't have written the article if it was bad). I've also used Elasticsearch, and I reckon that's pretty damn amazing. Anyone wanting more in-depth information should read or watch this FTS presentation from last year. It's by some of the people who has done a lot of work on the implementation, and talks about 9.6 improvements, current problems, and things we might expect to see in version 10. https://www.pgcon.org/2016/schedule/events/926.en.html There's also some previous presentations on the same topic which are interesting. You can see the RUM index (which has faster ranking here): https://github.com/postgrespro/rum