Backendless SQL data notebooks. Explore your data with SQL and Python and gain insights instantly.
SELECT region, SUM(revenue) AS total
FROM 'sales.parquet'
GROUP BY regionSELECT region
FROM regional_revenue
WHERE total > 2000000Under the hood
Everything runs locally in your browser via WebAssembly. DuckDB handles SQL (mostly PostgreSQL-compatible), Pyodide handles Python, and your data never leaves your device.
On top of that, we built a lightweight notebook UI that orchestrates cell execution. Notebooks and local files are stored in your browser via IndexedDB. Notebooks are saved as nbformat v4.5, so they're compatible with standard Jupyter tooling and renderers.
Each SQL cell behaves like a dbt model. It materializes a named view automatically, and you can reference it in later cells.
SQL handles most of the workflow. When you need something more flexible, drop into Python. Use the @sql_func decorator to expose Python functions as UDFs in your SQL queries.
Every view is instantly available in Python as a Pandas DataFrame. The view name becomes the DataFrame name.
Views, columns, types, and Python variables are always visible in the sidebar for easy debugging.
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No account needed. Your data never leaves your device.