Hex

Hex is what happens when someone rebuilds the data notebook around how analytics teams actually work: SQL first, Python when needed, results that stakeholders can open without installing anything. It sits deliberately between Jupyter's flexibility and a BI tool's shareability, and its Magic AI features have matured from demo to daily driver.

What we like

The polyglot notebook is the core win — a SQL cell feeding a Python cell feeding a no-code chart cell, with dataframes flowing between them, matches real analytical workflows better than either pure-SQL or pure-Python tools. Magic AI earns its name mostly because it is schema-aware: asking it to write a query against your actual warehouse tables produces usable SQL far more often than pasting DDL into a chatbot. Publishing a notebook as an interactive app — with inputs, filters, and scheduled refreshes — quietly eliminates the screenshot-into-slides ritual that wastes analyst hours everywhere. Version history and review flows make notebooks feel like engineering artifacts rather than scratchpads.

Where it falls short

Per-editor pricing around $36/month is fair for a core data team and painful the moment you want every analyst-adjacent person editing; watch how quickly "just add them as an editor" adds up. Business users remain consumers here — if your goal is self-serve analytics for non-technical staff, ThoughtSpot-style search or a semantic layer is the better bet. And teams wanting locked-down, pixel-perfect executive dashboards will still end up running Hex alongside a traditional BI tool rather than instead of one.

Verdict

For data teams of two to fifty, Hex is arguably the best working environment money can buy right now — the notebook UX, AI assist, and app publishing compound into real weekly time savings. Individuals can live happily on the free tier. Just be clear-eyed that it augments, rather than replaces, governed BI in most organizations.