http://gothub.r4focoma7gu2zdwwcjjad47ysxt634lg73sxmdbkdozanwqslho5ohyd.onion/unum-cloud/usearch
Moreover, unlike older approaches indexing high-dimensional spaces, like KD-Trees and Locality Sensitive Hashing, HNSW doesn't require vectors to be identical in length.
They only have to be comparable.
So you can apply it in obscure applications, like searching for similar sets or fuzzy text matching, using GZip compression-ratio as a distance function.