
Hex
FreemiumAI analytics platform combining SQL, Python, and no-code tools in collaborative notebooks and shareable data apps for entire teams.
What is Hex?
Hex unifies data exploration and sharing in one workspace: analysts write SQL and Python in a notebook, a Notebook Agent writes, edits and debugs code alongside them, and the result publishes as a polished interactive app that business users can filter and explore without touching the underlying code. That last step is the differentiator, since it removes the usual gap between an analyst's notebook and a stakeholder-ready deliverable. Two considerations. Hex has moved most pricing behind a sales conversation, with a free Community tier for individuals and paid tiers reported in the mid-thirties to seventy-plus per editor monthly, and SSO gated to Enterprise, which is a real cost for small teams with IT policies requiring it. Compute beyond the included medium tier and AI features bill as usage, so spend grows past seat count. Notebooks also use a proprietary format rather than standard .ipynb.
Key Features
How to Use Hex
✅ Best For
- Data engineers and analysts who want to write SQL and Python in one environment and share polished, interactive reports with stakeholders without switching to a separate BI tool.
- Data teams at companies like Notion or Ramp that need a governed self-serve analytics layer so business users can ask their own questions against live warehouse data.
❌ Not For
- Non-technical business users who have no data warehouse and need a simple drag-and-drop dashboard tool without any SQL or Python involvement.
- Solo analysts or freelancers looking for a low-cost, lightweight option, as Hex's collaborative features and pricing are optimized for teams.
Reviews
No reviews yet. Be the first to review Hex!
Pricing
- ✓Personal projects
- ✓limited projects and compute
- ✓Solo workflows
- ✓AI features
- ✓more projects
- ✓Full collaboration
- ✓Threads
- ✓scheduling
- ✓dbt integration
- ✓HIPAA
- ✓single-tenant
- ✓SSO
- ✓dedicated support
Prompts to Try
Analyze my Snowflake sales table and identify top 10 customers by lifetime value
Write a Python script to clean this dataset and remove outliers
Build a weekly active users trend chart from our event logs
Create a cohort retention analysis for Q1 signups
Summarize this month's revenue metrics for a non-technical stakeholder