SQL Workbench

Hey Product Hunt 👋 SQL Workbench is a free tool for online data analysis & data visualization, which is focussed on ease-of-use and data privacy. It offers a wide range of functionalities: ⌨️ Data Querying You can either load local CSV, JSON, Parquet or Arrow files, or load them from remote HTTP(S) or object storage sources (S3 compatible, Azure Blob Storage). It's also possible to directly attach remote DuckDB databases. 📊 Data Visualization There's a large variety of configurable visualizations, e.g. bar, line and area charts, maps, scatter plots, sunburst diagrams and more. ⚡ Performance It supports the analysis and visualization of large datasets up to multi-million records, without having to run infrastructure. ✨ Extensions It uses DuckDB WASM internally, so you can install and use all the extensions DuckDB provides, for example you can use the spatial extension to query remote geo data in various formats (see https://duckdb.org/docs/api/wasm...). ➰ Shareability You can easily share your data analysis' SQL code, and even include the visualization configurations via URL. 💻 Bring your own AI You can integrate a Text-to-SQL model running on your local machine via Ollama that supports SQL query generation from natural language. 📒 Data models It automatically generates ERD diagrams from the created tables. If you're curious how to use it, there's an intro into its usage at https://tobilg.com/using-duckdb-... containing basic but also more complex use cases and examples. For the impatient, here are some example queries: 🔗 Read data from Google Sheets 🔗 Query the GitHub Events API 🔗 Read remote Parquet files 🔗 Read remote CSV data 🔗 Read geo data from Shapefile

Hey Tobi, SQL Workbench looks like a powerful tool for data analysis and visualization. I'm particularly interested in the data privacy aspect: - How do you ensure that no data leaves the user's machine? - Also, how seamless is the integration with local Text-to-SQL models? Thanks for sharing this!

SQL Workbench has always done a great job of flexibility, compatibility, and scalability. AI is used to quickly turn natural language into SQL, and the accuracy rate is also very high. It also supports a variety of visualizations, and you can also share the SQL running results with other people, which is great!