pgsink VS opencv_py

This is a really awesome project. I’ve used it on https://github.com/lawrencejones/pgsink to generate type safe bindings to the Postgres catalog tables, along with a few of the tables the project maintains itself.

pgx is really good: it's what I used to write logical decoders in https://github.com/lawrencejones/pgsink

It used to be that companies would write their own hacky scripts to perform this extraction - I've had terrible incidents caused by ETL database triggers in the past, and even built a few generic ETL tools myself.

Postgres change-capture device that supports high-throughput and low-latency capture to a variety of sinks (at first release, just Google BigQuery):

https://github.com/lawrencejones/pgsink

I know there's debezium and Netflix's dblog, but this project aims to be much simpler.

Forget about kafka and any other dependency: just point it at Postgres, and your data will be pushed into BigQuery. And for people with highly-performance-sensitive databases, the read workload has been designed with Postgres efficiency in mind.

I'm hoping pgsink could be a gateway drug to get small companies up and running with a data warehouse. If your datastore of choice is Postgres, it's a huge help to replicate everything into an analytics datastore. A similar tool has helped my company extract expensive work out of our primary database, which is super useful for scaling.

The project is 90% there, about 10hrs and some testing away from being useable. Once there, I'll be hitting up some start-up friends and seeing if they want to give it a whirl.

Using this script: https://github.com/ctrager/opencv_py/blob/master/hummingbird...