8 million rows in. 600,000 out. 5.7 seconds. On a 16GB RAM laptop.

Duckle joined 4 sources at 2M rows each - an ADBC (Arrow) source, a CSV file, a MySQL table, and a second ADBC source - through one visual mapper: a 3-way join, 9 expressions, and a filter, straight to Parquet.

No cloud. No servers. Just Duckle on your laptop/desktop. This is what local-first data engineering looks like now.

Repository: https://github.com/SouravRoy-ETL/duckle

It pretty much holds good as of now. We are currently in a very early stage.

We are working hard to create an alternative to DuckDB and keep it completely open Source. No paid support like DuckDB, ClickHouse, etc.

Thanks bruh!

We are going to publish results real soon. Stay tuned!

Hehe! Irony leads the way!

Haha! Sloth's are actually faster than duck in Water!

I am working on Publishing Results soon in a day or two stay tuned and thanks for the kind words

It is becoming impossible to work with Opus 4.7. The calculations Opus 4.7 is making is not adding up and hence we feel like it is hallucinating. May be they tuned down RAG, context secretively.

I'm not clear on the actual use case how can this be leveraged?

It's for publishing and developing open-source software, I guess that's how it'll be "leveraged"?