Awesome-Adoption VS QuestDB

This last week of Hacktoberfest, I finished my last pull requests. I solved an issue for a Pet Adoption site built with React. The other pull request involved supporting count(1) for an SQL database queries in QuestDB.

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!