postgres-operator VS QuestDB

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.

If your data lacks uniform time intervals between consecutive entries, QuestDB offers a solution by allowing you to sample your data. After that, MindsDB facilitates creating, training, and deploying your time-series models.

If you're interested in that functionality or have any other feedback, please drop by our open source repository or community Slack and let us know.

QuestDB is a high-performance time series database with SQL analytics that can power through market data ingestion and analysis. It's open source and integrates well with the tools and languages you use. Check us out!

Looks like full keys are always compared if hash codes test equal, which is what I'd expect. For example: https://github.com/questdb/questdb/blob/master/core/src/main...

But of course, I want to run a QuestDB instance on my node, which uses two additional TCP ports for Influx Line Protocol (ILP) and Pgwire communication with the database. So how can I expose these extra ports on my node and route traffic to the QuestDB container running inside of k3s?

In this post, I will detail a way in which I recently used annotations while writing an operator for my company's product, QuestDB. Hopefully this will give you an idea of how you can incorporate annotations into your own operators to harness their full potential.

QuestDB is an open source, high performance time series database. With its massive ingestion throughput speeds and cost effective operation, QuestDB reduces infrastructure costs and helps you overcome tricky ingestion bottlenecks. Thanks for reading!