Hex vs Bruin
Complete Comparison
An honest comparison between Hex and Bruin to help you choose the right AI data analyst for your team.
| Feature | Hex | Bruin |
|---|---|---|
| Conversational AI in Slack/Teams | ||
| Collaborative Notebooks | ||
| Natural Language to SQL | ||
| Self-Serve for Non-Technical Users | Via published apps | |
| Open Source | ||
| Data Ingestion | ||
| Data Transformation | ||
| Data Quality Checks | ||
| Data Lineage | ||
| Self-Hostable | ||
| WhatsApp Integration | ||
| Pricing | Per-seat SaaS | Free + Cloud plans |
Core Philosophy
Different Approaches to AI Analytics
Hex
Hex is a collaborative data workspace built around notebooks that combine SQL, Python, and no-code blocks. Hex Magic adds AI to help analysts write queries, explain results, and build data apps for sharing with stakeholders.
- Notebook-first: SQL and Python cells in a collaborative workspace
- Hex Magic: AI assistance for writing queries and explaining data
- Data apps: Publish notebooks as interactive apps for non-technical users
- Built for analysts: Designed for data teams, not end-users
- Standalone web app: Users log in to Hex to view results
Best suited for data teams that want a modern notebook environment and publish curated data apps to stakeholders who log in to consume them.
Bruin
Bruin is a conversational AI data analyst that lives where your team already works — Slack, Microsoft Teams, Discord, WhatsApp, and browser — plus a full data pipeline platform for ingestion, transformation, and quality.
- Where you work: Slack, Teams, Discord, WhatsApp, and browser — no new app to adopt
- Conversational AI: Anyone can ask questions in natural language, no notebook required
- Full pipeline: Ingestion, transformation, quality checks, lineage
- Open source: CLI and ingestr are open-source with 200+ connectors
- Flexible deployment: Self-hostable or managed cloud
Best suited for teams where business users (not just analysts) need self-serve answers from data, plus a unified pipeline — without a separate BI app to log into.
Architecture
How They Work
Hex Workflow
Typical Hex Workflow:
- 1.Analyst logs in to Hex and opens a notebook
- 2.Writes SQL or Python, uses Magic AI to assist
- 3.Builds charts and inputs into an interactive app
- 4.Publishes the app and shares a link
- 5.Stakeholders log in to Hex to use the app
Result: Powerful for data teams, but non-technical users still depend on analysts to build and publish an app before they can get an answer.
Bruin Workflow
Bruin Workflow:
- ✓Ask @Bruin in Slack, Teams, Discord, WhatsApp, or browser
- ✓Bruin writes and runs SQL, returns the answer inline
- ✓Follow up with questions in the same thread
- ✓Full data pipeline: ingestion, transformation, quality
- ✓200+ connectors and column-level lineage
Result: Business users get answers without waiting for an analyst to build a notebook — and the data team still has a full pipeline underneath.
User Experience
Who Uses It & How
Hex
Built for Data Teams
Analysts write notebooks; business users consume published apps. Ad-hoc questions still go through the data team.
Adoption Considerations:
- • Non-technical users need a published app to self-serve
- • Every new question often means new notebook work
- • Stakeholders must log in to a separate workspace
- • No native Slack/Teams conversational interface
- • Best-in-class if your team already loves notebooks
Challenge: Data teams become a bottleneck — every new business question is a new notebook or app to build.
Bruin
Self-Serve for Anyone on the Team
Bruin lives in Slack and Teams. Business users ask questions directly — no notebook, no app, no handoff.
Why Adoption Is Effortless:
- ✓ Conversational interface everyone understands
- ✓ Answers appear where decisions are made
- ✓ Unblocks analysts from ad-hoc requests
- ✓ Thread-based follow-ups for deeper analysis
- ✓ Browser option for standalone exploration when needed
Advantage: Business teams self-serve; data teams stop being a ticket queue.
Pricing
Pricing & Value
Hex
Per-User SaaS Pricing
Hex charges per editor and per viewer. Costs grow as more people consume published apps.
Cost Considerations:
Editor + Viewer Seats
Separate tiers for creators and consumers of notebooks
Closed Source
Hex is a proprietary SaaS product — no self-host option
Add-On for AI
Magic AI capabilities sit on top of the base subscription
No Pipeline Included
Ingestion and transformation require other tools like Fivetran and dbt
Note: Hex offers a generous free tier for small teams, but pricing scales with seats as adoption grows.
Bruin
Free Open-Source Core + Affordable Cloud
Start free with the open-source CLI and scale with cloud plans as needed.
Pricing Advantages:
Free Open-Source Core
CLI and ingestr are fully open-source and free to use
No Per-Seat Pressure
Pricing that doesn't penalize you for adding more users
Pipeline Included
Ingestion, transformation, quality, lineage — no extra stack needed
Self-Hostable
Run on your own infrastructure for full control and cost efficiency
Advantage: One platform for pipeline + AI analyst — no separate notebook and BI subscriptions stacking up.
Decision Guide
When to Choose Each Tool
Choose Hex if...
Your analysts live in notebooks
You want a modern SQL + Python notebook environment with collaboration and versioning.
You publish curated data apps
You want to turn notebooks into polished, interactive apps for specific stakeholder workflows.
You already have a pipeline
Fivetran + dbt + warehouse is solved for you, and you just need an analysis layer on top.
Choose Bruin if...
Business users need self-serve answers
Ops, sales, and live ops teams should get answers in Slack without filing a ticket to the data team.
Your team lives in Slack, Teams, or WhatsApp
Get answers where conversations and decisions already happen — no context switching.
You need pipeline + AI analyst in one
Ingestion, transformation, quality, lineage, and AI analyst unified — no separate notebook tool.
You prefer open source
Want transparency, community-driven development, and the ability to self-host.
You want to avoid per-seat scaling costs
Adding more viewers shouldn't mean a bigger SaaS bill every quarter.