Postgres Queues Actually Scale

Postgres-backed queues can support high-throughput workloads despite their reputation for poor scalability when contention, transaction behavior, and index overhead are addressed carefully. A system described by DBOS reached more than 30,000 workflow executions per second across thousands of servers by using `FOR UPDATE SKIP LOCKED` to let concurrent workers claim distinct queued jobs without competing for the same rows, avoiding the severe bottleneck of naive polling. It then reduced serialization failures by using the stricter REPEATABLE READ isolation level only for queues requiring global concurrency limits, while using READ COMMITTED for queues with local limits. Finally, it lowered CPU and autovacuum costs by redesigning indexes to match dequeue ordering, using partial indexes only for relevant workflow states or records, and reducing unnecessary index maintenance during workflow updates.

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