DBOS is amazing when it comes to Durable Workflows. There are others in the space - the most popular one being Temporal but I argue, Temporal is also the most complicated one. I often say Temporal is like Kubernetes while DBOS is like `docker compose`. (and for those taking me literally, you can use DBOS in Kubernetes!)

I don't realize why DBOS is not nearly as popular as Temporal but it has made a world of difference building Durable Queues and Long Running, Durable Workflows in Python (it supports other languages too).

As they show in this article, Postgres scales impressively well (4 billion workflows per day, on a db.m7i.24xlarge, enough for most applications), which is why, if you have your PostgreSQL backup/restore strategy knocked out and dialed in, you should really take a close look at DBOS to handle your cloud agnostic or self hosted Durable Queues and Durable Workflows. It's an amazing piece of software founded by the original author of Ingres (precusor to Postgres - the story of DBOS itself is captivating. I believe it started from being unable to scale Spark job scheduling)

when discussing DB it becomes so so interesting not because db itself but the people trying to ask some infeasible questions

Yes, you can scale it quite well vertically.

But how about horizontally? It would be nice to have high availability, or even to be able to upgrade the OS and postgres itself without downtime.