ABabelanger·Dec 10, 2024
Disclaimer: I'm a co-founder of Hatchet (https://github.com/hatchet-dev/hatchet), which is a Postgres-backed task queue that supports durable execution.
> Because a step transition is just a Postgres write (~1ms) versus an async dispatch from an external orchestrator (~100ms), it means DBOS is 25x faster than AWS Step Functions
Durable execution engines deployed as an external orchestrator will always been slower than direct DB writes, but the 1ms delay versus ~100ms doesn't seem inherent to the orchestrator being external. In the case of Hatchet, pushing work takes ~15ms and invoking the work takes ~1ms if deployed in the same VPC, and 90% of that execution time is on the database. In the best-case, the external orchestrator should take 2x as long to write a step transition (round-trip network call to the orchestrator + database write),
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so an ideal external orchestrator would be ~2ms of latency here.
There are also some tradeoffs to a library-only mode that aren't discussed. How would work that requires global coordination between workers behave in this model? Let's say, for example, a global rate limit -- you'd ideally want to avoid contention on rate limit rows, assuming they're stored in Postgres, but each worker attempting to acquire a rate limit simultaneously would slow down start time significantly (and place additional load on the DB). Whereas with a single external orchestrator (or leader election), you can significantly increase throughput by acquiring rate limits as part of a push-based assignment process.
The same problem of coordination arises if many workers are competing for the same work -- for example if a machine crashes while doing work, as described in the article. I'm assuming there's some kind of polling happening which uses FOR UPDATE SKIP LOCKED, which concerns me as you start to scale up the number of workers.