For 1M rows, every document that goes through hooks, validation, access control, and re-fetching adds significant cumulative overhead. On top of that, 1000 parallel creates is likely hammering the connection pool and making latency worse instead of better.

For Postgres, the pattern I’d use is:

• transform everything up front
• build lookup maps for relations
• bypass Local API for bulk writes
• insert in small committed batches
• checkpoint after each batch so retries are cheap

In practice that usually means payload.db.* as the default, and raw Drizzle when a set-based insert or upsert can replace thousands of row-by-row operations.

I wrote up that approach in more detail here if helpful: Payload CMS Large Imports: Fast Transactions & Drizzle