I am using the HNSW (Hierarchical Navigable Small World) index structure in PolarDB for vector similarity search via the pgvector extension.

HNSW is fundamentally a graph-based index, and I have two related questions:

1. When building an HNSW index, does the order of vector insertion affect the final index quality? For example, could random insertion vs. bulk ordered insertion lead to differences in search accuracy or recall?

2. Could PostgreSQL's VACUUM, ANALYZE, or tuple visibility mechanisms (MVCC) potentially affect the internal graph connectivity or performance of the HNSW index, especially in scenarios with frequent updates or deletions?

I would like to know whether these factors need special consideration in production, and if there are recommended ways to mitigate potential issues?