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.

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levkk 2 hours ago | parent | next [-]

Shameless plug[0].

[0] https://pgdog.dev

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tuvix 5 hours ago | parent | prev | next [-]

Only played around with it but you can use patroni, etcd and HAproxy to achieve this. It’s a pain, but I believe there was some kind of coolify-style open source application to do this for you but I can’t for the life of me remember its name

	▲	jrnkntl 5 hours ago \| parent \| next [-]
		autobase[1] is the one I can think of [1] https://github.com/autobase-tech/autobase
	▲	subhobroto 5 hours ago \| parent \| prev [-]
		You might be thinking of Pigsty? Atleast I hope you are! Nothing else has been as well battletested. Unfortunately, perhaps because if its name, it gets no facetime on HN. Its last few mentions here barely received attention it deserved.

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levl289 5 hours ago | parent | prev | next [-]

Yep, this is what I think about when “scaling” is mentioned. Maybe I’m too distributed-compute brained, but throwing CPU at a db isn’t what I was hoping would be the answer.

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_3u10 5 hours ago | parent [-]

So the point of distributed compute is to reduce the compute needed? I’ve generally found that distributed compute requires more compute than vertical scaling while getting clobbered by network bandwidth / latency.

Theoretically with 2 to 10x compute required and in practice 100 to 500x

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literalAardvark 4 hours ago | parent [-]

The point of distributed computing is to do computing that you can't do on a vertically scaled system or to increase availability.

If you're doing it for other reasons it's usually a mistake.

	▲	raddan 2 hours ago \| parent [-]
		The advice I’ve gotten is that you want to move computation to data that is already distributed. The cost of moving large amounts of data usually dwarfs compute costs (usually, not always), and so the performance win comes from distributing the computation and then (depending on the problem) centralizing aggregate results.

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literalAardvark 4 hours ago | parent | prev [-]

Practically trivial to do in 2026 even by hand, and there are a couple of ready to use solutions that even make it automated.

If you're running it in kubernetes with cloudnativepg it's even easier.

The only thing it doesn't do well is master master replication which is why most of these does it scale posts mostly talk about how slow writes are. And they are pretty slow.