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Dev tools · February 17, 2026

DS

Data Studio – Open-Source Data Notebooks

Hey HN, I am Alex. I am open sourcing Data Studio, a lightweight data exploration IDE in your browser that runs locally. Try it: https://local.dataspren.com (no account needed, runs locally) More information: https://github.com/dataspren-analytics/data-studio I love working with data (Postgres, SQL, DuckDB, DBT, Iceberg, ...). I always wanted a data exploration tool that runs in my browser and just works. Without any infra or privacy concerns (DuckDB UI came quite close). Features: - Data Notebooks - SQL cells work like DBT models (they materialize to views) -…

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In plain words

Data Studio is an open-source, browser-based IDE for data exploration that runs locally without requiring infrastructure or accounts. It supports SQL notebooks where cells materialize to views like DBT models, allows Python functions within SQL queries, and enables direct use of database views as dataframes. Users can work with Postgres, DuckDB, and other databases, plus transform and format Excel, CSV, Parquet, and JSON files. Designed for data analysts and engineers who want privacy-conscious, lightweight data work in their browser.

written from the facts on this page · September 2026

From the sources

In the maker’s words, at launch

Hey HN, I am Alex. I am open sourcing Data Studio, a lightweight data exploration IDE in your browser that runs locally. Try it: https:&#x2F;&#x2F;local.dataspren.com (no account needed, runs locally) More information: https:&#x2F;&#x2F;github.com&#x2F;dataspren-analytics&#x2F;data-studio I love working with data (Postgres, SQL, DuckDB, DBT, Iceberg, ...). I always wanted a data exploration tool that runs in my browser and just works. Without any infra or privacy concerns (DuckDB UI came quite close). Features: - Data Notebooks - SQL cells work like DBT models (they materialize to views) - Use Python functions inside of SQL queries - Use DB views directly in Python as dataframes - Transform Excel files with SQL - You can open .parquet, .csv, .xlsx, .json files nicely formatted If you like what you see, you can support me with a star on Github. Happy to hear about your feedback <3

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