Parallel Segmented Backfills for Postgres
Parallel Segmented Backfills split Postgres tables into row segments by integer primary key and backfill them in parallel as an alternative to CTID scans.
CTID-based backfills are fast and efficient - especially for large, append-only Postgres tables. They scan directly by physical row location, often outperforming logical queries in stable datasets.
But CTIDs come with tradeoffs: they’re slow to initialize for large tables, fragile in dynamic tables where rows update or move, and they can time out in environments with aggressive statement_timeout settings.
For teams working with massive, constantly changing Postgres tables, these limitations can stall backfill progress or create reliability risks.
Parallel Segmented Backfills offer an alternative path. Instead of relying on CTID, Artie slices tables into logical row segments based on integer primary keys - then parallelizes the work across those chunks.
The result: similar performance to CTID backfills, but with stronger guarantees in dynamic environments.
We recently helped a customer backfill 8 billion rows in an actively updated Postgres table. CTID-based scans kept timing out and drifting. With Parallel Segmented Backfill, we split the workload across logical row ranges and completed the job - no timeouts, no skipped rows, no guesswork.
Why this matters:
- Resilient to updates and vacuuming - row movement doesn’t break backfills
- Offers CTID-level performance with better reliability under load
- Avoids statement_timeout failures in large or busy tables
- Makes backfill behavior predictable and tunable