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Ask HN: Best way to ingest data, run code/notebooks, and display dashboards?

1 点作者 raihansaputra10 个月前
I have a need to ingest files, run Python Notebooks&#x2F;files (pandas etc) on it, and output to database, files and dashboard(s). Ideally the runs&#x2F;executions can be graphed and versioned in case the code&#x2F;data changes for re-runs.<p>I keep exploring ETL&#x2F;ELT&#x2F;DAG&#x2F;MLOps tools and all seem to be very complicated or enterprise-priced gated.<p>I don&#x27;t mind buliding out another web app to ingest the data to S3 and&#x2F;or display from database, but ideally it&#x27;s integrated.<p>Some I&#x27;ve read into:<p>- Windmill: The most suited except that the Apps portion also needs users to be subscribed to the workspace (even for self-hosted). Can be worked around by another web app to upload to an S3 bucket and ingest from there. The enterprise offerings are eyewateringly expensive for non-first world businesses.<p>- Pachyderm: Interesting offering as they focus on data-versioning and data pipeline, but unsure about the dashboard part.<p>Airflow, dagster, temporal, prefect, etc are a bit too code-heavy for my use case. I want the graphs and the larger logic flows to be understandable by non-data engineers.<p>I don&#x27;t have any large volume to deal with, so ideally something that can be run on one machine as a default and scale as needed. Clarity, dependability, and simplicity of deployment are the priorities.<p>Any suggestions?

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