This is comparing apples and oranges. You've pointed to some technologies from vector database vendors. Neon isn't a vector database vendor. They're a Postgres vendor. The objective of pg_embedding, pg_vector, and others is to offer teams who deploy Postgres the opportunity to use their existing infrastructure for vector search. The added and important benefit here is hybrid search: using existing DB data to filter semantic search results.

What the work done by Neon, the pgvector team, Supabase and others points to is that "speed" isn't the only factor in vector database selection. Developer experience and existing infrastructure investment are too.