Hex

Hex is a modern collaborative data workspace that enables data analysts, data scientists, and engineers to work together in a shared notebook environment that combines SQL, Python, and R with interactive application publishing capabilities. By bridging the gap between exploratory analysis and production data applications, Hex has become a popular tool for data teams that want to move beyond static dashboards toward interactive, self-service data experiences.

The Hex notebook combines SQL cells and Python/R cells in a flexible, ordered sequence. SQL cells query any connected database or warehouse directly, returning results as dataframes that are immediately available in subsequent Python or R cells. This seamless SQL-to-Python flow eliminates the manual data export and import steps that slow down analysis workflows in tools that separate SQL and code environments.

The reactive execution model in Hex is one of its most distinctive features. When a cell is modified and run, Hex automatically re-runs all downstream cells that depend on its output, keeping the entire notebook consistent. This reactive behavior makes it much easier to iterate on analyses, as changing a filter or parameter propagates through the entire notebook automatically.

Input components such as sliders, dropdowns, text inputs, date pickers, and checkboxes can be added to any Hex notebook to create interactive controls. When an input value changes, the reactive execution model re-runs all cells that reference that input, effectively turning a notebook into an interactive application. This capability enables creating self-service analytical tools where non-technical users can explore data by adjusting parameters without writing code.

Published Hex Apps present the notebook as a clean, polished application interface where all code cells are hidden and only the inputs, charts, and data tables are visible. Apps can be shared with stakeholders via a URL, embedded in internal portals, or scheduled for periodic delivery via email. The transition from analysis to a shareable application requires no additional development work beyond publishing the notebook.

The magic AI feature in Hex uses large language models to help analysts write SQL queries, generate Python code, debug errors, and explain code. This AI assistance is contextually aware of the database schema and previous cells in the notebook, making suggestions that are relevant to the specific analysis being built.

Hex connects to all major data warehouses and databases including BigQuery, Snowflake, Redshift, Databricks, PostgreSQL, MySQL, Dremio, and others. Projects can also connect to uploaded CSV files, Google Sheets, and REST APIs for broader data access.

The collaboration features in Hex include real-time multi-user editing, inline comments on cells and visualizations, version history, and scheduled runs that keep notebooks and apps updated with fresh data automatically.