1. Simpler architecturally. Just a normal Python process versus a workflow server coordinating multiple workers.
2. Easier dev/debugging. A Temporal program is essentially distributed microservices, with control flow split between the workflow server and workers. That complicates any testing/debugging because you have to work through multiple components. Whereas DBOS is just your process.
3. Performance. A state transition in DBOS requires only a database write (~1 ms) whereas in Temporal it requires an async dispatch from the workflow server (tens-hundreds of ms).
https://github.com/abtinf/temporal-a-day/blob/main/001-all-i...
Ignoring my setup, I'm a bit confused from the website if I can run this as a library? Seems that I need to use your SaaS backend to get started? Or did I misunderstand the flow from my quick flow?
And yes, you can absolutely run this locally as a library! The bottom half of the quickstart covers how to do it: https://docs.dbos.dev/explanations/system-tables Just use a local (or Docker) Postgres.