For that particular usage, the volume we process and business criticality make it a good choice for inventing here - but for other durable processes we just use off the shelf tools since the cost of maintenance would quickly outstrip the value.

Postgres is a great tool to use and far more powerful than most people give it credit for - but there's always the balance of in-house maintenance vs. paying rent for someone else's solution.

Not sure where the NIH ends and where you're actually better off with a supported orchestration approach. I suppose if you expect your program to be around a while (or need advanced features), maybe think about using something a bit more battle tested?

Strong correctness guarantee is something that should not be undermine. Even more important than availability.

The examples on the website is simple but heavily undermines the importance of correctness. Anyone who implement similar pseudo-code directly will eventually suffer from data correctness issue in crashes.

  @DBOS.workflow()
  def checkout_workflow(items: Items):
      order = create_order()
      reserve_inventory(order, items)
      payment_status = process_payment(order, items)

      if payment_status == 'paid':
          fulfill_order(order)
      else:
          undo_reserve_inventory(order, items)
          cancel_order(order)

Given the above, it would seem that durable workflow software is pushed forward by those who have a surplus of VC money to spend. As for the vendors, there is no shortage of people trying to sell you things that you don't need.

Typescript: https://www.pgflow.dev

Elixir: https://github.com/agoodway/pgflow/blob/main/docs/COMPARISON...