Running Durable Workflows in Postgres Using DBOS

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The discussion around DBOS revolves around its effectiveness as a workflow engine for Postgres, emphasizing the importance of control over workflow management and the potential drawbacks of using an external orchestrator. Key highlights include the speed of DBOS compared to traditional orchestrators (like AWS Step Functions), with exact-once execution for database transactions. Users express concerns about how workflows manage error states, particularly in scenarios where systems go down or operations time out. Moreover, there is interest in how DBOS stacks up against established tools like Celery and Dagster in terms of running distinct workflows and managing worker coordination. Users also want to know more about getting data in and out of workflows, the idempotency assurance, and the difference between using DBOS and other platforms with Postgres as a backend.
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