amphi-etl

Amphi is a visual, low-code canvas for building data pipelines that compile down to real Python. You drag components onto a board to clean, join, and reshape data, and under the hood it generates pandas and DuckDB code, so you're not locked into a black box. It runs standalone or as a JupyterLab extension, connects to CSVs, Postgres, Snowflake, and REST APIs, and it's free to use.

Getting started is easy: pip install, `amphi start`, and you're in the canvas. No GPU, just a Python environment. The catch on setup is scope, it's built for lightweight ETL and data prep, not heavy-duty distributed processing, so match the tool to the size of the job.

For analysts and developers who want Alteryx or KNIME-style visual data prep without the enterprise license, this is a useful free option, solo or small team. The fact that it emits readable Python means you can graduate a pipeline out of the visual tool and into code when you outgrow it.

The catch is the license. Amphi is under the Elastic License v2, which is source-available, not truly open source. You can self-host and use it freely for your own work, but you can't turn around and offer it as a competing hosted service. For most internal use that's a non-issue, just know it's not MIT or Apache before you build a product on it.