Founder here. Thanks for the interest! We built Moose because we were tired of the complexity involved in setting up and maintaining data pipelines.

What makes Moose different is how it simplifies the entire workflow - from ingestion to processing to serving data through APIs. We've found teams spend too much time wiring together different tools rather than focusing on the actual data insights.

The local development experience was a big focus for us. You can instantly test your changes with real data without waiting for deployments. And we've made sure the same code runs identically in production to eliminate those frustrating "works on my machine" moments.

Happy to answer any questions about our technical approach or how we're handling specific use cases. We're particularly interested in hearing about pain points you've experienced with existing data systems or any feedback you might have on Moose.

Very cool to see what used to take a team years to build in a simple, intuitive OSS package. Getting a stack like this up and running in 20 lines of python out of the box would have been unthinkable 10 years ago. Congrats to the team. Can't wait to see where you take this!

Very cool, going to try this in our next internal build sprint :)

I’d brand this OS Tinybird.

Impressive team behind this. Excited to see what they cook up.

This is sick, insane shipping speed from these guys

I think Moose is onto something—it simplifies data pipelines by abstracting away the complexity. I really like it. Very clever!

Impressive work done by Team!

Honestly, I was just so over the nonstop ETL and data wrangling grind. I just wanted to build stuff that actually shows results and not waste half my day setting up pipelines. That’s how I ended up using Moose in one of my prototypes. It’s been awesome seeing it cut through the noise and let me skip the annoying setup so I can get straight to building features that actually matter. Cool stuff - cheers!

[dead]

[dead]