postgres-operator VS pg_ivm

yes, precisely. It's UI part that's broken, which cannot list snapshots. Issue is here, no fix since 2020, sadly: https://github.com/zalando/postgres-operator/issues/937

I personally like the Zalando operator better, you can add databases and users by updating the CRD, feature parity between the two on HA is pretty good

https://github.com/zalando/postgres-operator

one of the solutions which made it pretty simple for us to run postgresql in a ha environment (mostly in k8s, but works standalone as well) is zalandos patroni: https://github.com/zalando/patroni it's really solid and worked for us for a few years already.

or for k8s their operator: https://github.com/zalando/postgres-operator (docker image: https://github.com/zalando/spilo) we've also tried other operators which were easier to get started, but they failed miserably (crunchyrolls operator is basically based on the zalando one)

git clone https://github.com/zalando/postgres-operator.git cd postgres-operator

Zalando / Postgres-Operator

Somewhere between here and here i found out about that.

Here's an example of using the PostgreSQL Operator to deploy a high availability PostgreSQL cluster in Kubernetes. In this example, I'll be using the PostgreSQL Operator from Zalando [https://github.com/zalando/postgres-operator] to deploy a PostgreSQL cluster with two nodes.

Here's the operator for a postgres cluster: https://github.com/zalando/postgres-operator

And that repo you linked to has 1846 issues, 161 open. Which doesn't seem extraordinary based on my limited exposure to k8s.

Another example: https://github.com/zalando/postgres-operator/issues with 445 open issues. Why?

Maybe I'm wrong and this is all a good sign of progress, but my impression is that the entire k8s ecosystem is held together with reused duct tape.

FTA, because I don't like Jeopardy questions in headlines:

“Incremental View Maintenance (IVM) provides a method for keeping materialized views current by calculating and applying only the incremental changes, as opposed to the complete recomputation of contents performed by the REFRESH MATERIALIZED VIEW command.”

Article shows using the pg_ivm Postgres extension available here: https://github.com/sraoss/pg_ivm

There is an extension that provides some limited incremental MVIEW refresh: https://github.com/sraoss/pg_ivm

There’s awesome work being done on incremental view maintenance in postgres:

https://github.com/sraoss/pg_ivm

It makes sense to perform managed denormalization - use a materialized view or automatically refresh a table or foreign server (via FDW) using common triggers (like pg_ivm does). And it's fine to add a TTL to it and use as a read store... update on user login and make a partial index just for that. And that's how you could get CQRS...