But it's still a wonderful example for how far you can get with brute-force vector similarity search that has been optimized like crazy by making use of SIMD. Not having to use a fancy index is such a blessing. Think of all the complexities that you don't have when not using an index. You don't have these additional worries about memory and/or disk usage or insert/delete/update costs and you can make full use of SQL filters. It's crazy to me what kind of vector DBs people put up with. They use custom query languages, have to hold huge indices in memory or write humongous indices to disk for something that's not necessarily faster than brute-force search for tables with <5M rows. And let's be honest who has those gigantic tables with more than 5M rows? Not too many I'd assume.