Hex vs Deepnote: Which Data Notebook for Your Team?

Pick Hex if you need to ship interactive data apps to stakeholders who will never read code. Pick Deepnote if your team lives in notebooks and wants real-time collaboration, schema-aware AI, and a lower bill. Both sleep after 15 minutes of inactivity, which matters more than either vendor's marketing page admits.

Side-by-side comparison

Where do they sit on the spectrum?

Both tools started as notebooks. They've drifted in opposite directions.

  Pure Notebook                                    Full App Platform
  |                                                             |
  |    Deepnote          Hex                                    |
  |       |               |                                     |
  v       v               v                                     v
  +-------+---+-----------+-------+----------+---------+--------+
  Jupyter     Deepnote    Hex     Streamlit   Retool    Fastero
              (collab     (apps +             (low-code (always-on
              notebook)   notebook)            builder) data apps)

Deepnote is a better Jupyter. Hex is a notebook that wants to be a BI tool. Neither is a deployment platform — and that distinction matters when you need something running at 3 AM without anyone's laptop open.

What does Hex's Generative Apps agent actually do?

Hex's biggest recent bet is Generative Apps, currently in beta. The idea: describe what you want ("show me a dashboard that tracks weekly churn by cohort"), and the agent generates a full interactive app — SQL queries, Python transformations, charts, input widgets — inside a Hex notebook. You review, tweak, and publish.

It's impressive in demos. In practice, the generated apps need editing. The agent sometimes picks the wrong chart type, writes SQL that's syntactically correct but semantically off, or creates layouts that look fine with sample data and fall apart with your real schema. Still, it's a genuine productivity shortcut for getting a first draft of an app in minutes instead of hours.

Deepnote has nothing equivalent. Their AI is focused on the notebook experience — suggesting code completions, explaining errors, auto-generating SQL from your schema. It's useful inside a notebook but it won't build you an app, because Deepnote doesn't have apps. Different bet, different outcome.

For a broader look at the app-building landscape: Best Data App Platforms in 2026.

How does collaboration actually differ?

Both tools support real-time multiplayer editing. Multiple people in the same notebook at the same time, cursors visible, no merge conflicts. But the collaboration philosophies diverge from there.

Deepnote leans into the document model. You can comment on individual cells, request reviews from teammates, and resolve threads — the same workflow you'd use in Google Docs. Notebooks feel like living documents that accumulate context through comments and discussion. For teams that do peer review on analyses before sharing results, this is well thought out.

Hex leans into the app delivery model. Collaboration features exist in the notebook, but the real sharing story is app mode. You build in the notebook, then publish an interactive app. Stakeholders interact with the app, not the notebook. There's less emphasis on "let's co-edit this analysis" and more on "let me build something and hand you a finished product."

If your team's workflow is "three analysts iterate on an analysis together, then share findings" — Deepnote's model fits better. If your workflow is "one analyst builds something, then 20 people use it" — Hex's model fits better.

What about pricing for a small team?

The pricing gap is real and it compounds as you add seats.

For a 5-person data team, billed annually:

• Deepnote Team: 5 editors x $39/month = $195/month = $2,340/year + AI credits
• Hex Professional: 5 editors x $36/month = $180/month = $2,160/year + compute + AI credits
• Hex Team: 5 editors x $65/month = $325/month = $3,900/year + compute + AI credits

The headline per-seat numbers look close at the Professional tier. But Hex's compute costs are separate, and the features most teams actually need — published apps with viewer permissions, granular scheduling, API access — live on the Team tier at $65/seat. Deepnote includes more at the base tier.

If you want SSO on Hex, you're pushed to Enterprise pricing ($80-120+/seat). Deepnote includes SSO on their Team plan. For regulated companies where IT mandates SSO on every vendor tool, this is a significant cost difference.

Deeper breakdown of Hex's pricing structure: Hex Pricing: Is It Worth It in 2026?

The 15-minute sleep problem

Both Hex and Deepnote sleep notebook kernels after roughly 15 minutes of inactivity. For interactive exploration — you're at your desk, running cells, tweaking queries — this is fine. The kernel stays warm while you're working.

The problem shows up when you need something running without a human watching it. A scheduled notebook wakes up, executes, produces results, and goes back to sleep. That works for batch reports. It does not work for:

• A data app that stakeholders check throughout the day (first load after idle = cold start delay)
• An alerting pipeline that needs to evaluate conditions continuously
• An internal tool that should respond instantly when someone opens it at 6 PM

  What happens when nobody's looking:
 
  Hex / Deepnote              Fastero
  +-----------+               +-----------+
  |  Active   | <-- user      |  Active   | <-- user
  |  kernel   |     typing    |  process  |     or trigger
  +-----------+               +-----------+
       |                           |
       | 15 min idle               | (no sleep)
       v                           |
  +-----------+                    |
  |  Sleeping |                    |
  |  kernel   |                    |
  +-----------+                    |
       |                           |
       | user returns              |
       v                           v
  +-----------+               +-----------+
  | Cold start|               |  Still    |
  | (seconds) |               |  running  |
  +-----------+               +-----------+

Scheduled execution papers over this for batch workflows. But if you're building something that needs to be alive — responding to webhooks, monitoring a data source for anomalies, serving an internal tool that 30 people hit unpredictably — the notebook model hits a wall.

Which AI assistant is better?

Hex Magic has been around longer and is tightly integrated with the notebook + app workflow. It can generate SQL, Python, charts, and (with Generative Apps) entire applications. It understands your connected data sources and can write queries against your actual schema.

Deepnote's AI agent is newer but takes a different angle: deep schema awareness. It indexes your connected databases, understands table relationships, and uses that context when suggesting code or answering questions. Ask it "how do I calculate monthly retention?" and it will reference your actual user and event tables, not generic SQL.

Both charge AI credits on top of the base subscription. Neither includes unlimited AI usage in the seat price.

If you want AI that builds apps, Hex is ahead. If you want AI that deeply understands your data model and helps you write better queries, Deepnote's approach is more targeted.

FAQ

Can I export my work from Hex? Yes, but with friction. Hex uses a proprietary notebook format. You can export to .ipynb, but the conversion is lossy — app layouts, reactive cell dependencies, and Hex-specific features don't survive. If you've built heavily in Hex's app mode, migrating away means rebuilding. Deepnote uses .ipynb natively, so your notebooks are portable from day one.

Does Deepnote have an app builder? No. Deepnote has presentation mode and can publish notebooks as read-only pages, but there's no interactive app mode with input widgets, layout builders, or stakeholder-facing interfaces. If turning analyses into apps is a core workflow, Deepnote is the wrong tool.

Can I connect both tools to my data warehouse? Yes. Both support Snowflake, BigQuery, Databricks, Redshift, and Postgres, among others. Hex lists 17 warehouse connectors. Deepnote covers similar ground plus S3 and dbt integration. Neither tool is likely to block you on connectivity.

Which one is better for a solo analyst? Deepnote's free tier is more generous — unlimited viewers and meaningful functionality before you pay. Hex's free tier limits you to one editor and restricts compute. For a solo analyst exploring data without a budget, Deepnote is the easier starting point.

Should I consider something other than both? If your actual bottleneck is getting analysis deployed and running reliably — not the notebook editing experience — then the problem isn't Hex vs Deepnote. It's that notebooks were designed for exploration, not production. Tools like Fastero sit in a different part of the stack: always-on data apps with event-driven triggers, no idle timeouts, and deployment built in from the start.

The bottom line

Hex is betting that notebooks should become apps. Deepnote is betting that notebooks should become better notebooks. Both are right for different teams.

Pick Hex if you regularly turn analyses into stakeholder-facing tools and want AI to help generate them. Pick Deepnote if your team collaborates heavily on analyses, cares about .ipynb portability, and doesn't need an app builder. Pick neither if what you actually need is a data app that stays on.

Related: Hex vs Mode: Analytics Notebooks Compared | Deepnote vs Hex vs Jupyter: Notebooks Compared | Best Data App Platforms 2026 | Hex Pricing: Is It Worth It in 2026?

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Last updated: August 2026.