Overview

Deepnote is a notebook workspace for data analysis, exploration, and machine learning, aimed especially at teams that need to collaborate and share working analyses. Its strongest case is the path from notebook to scheduled run, dashboard, app, or API; teams with only a few editors can start free, but paid capacity is priced per editor.

Key features

Notebooks, AI, and collaboration

The AI copilot can chat with data, generate charts, and write code, while notebooks support Python, SQL, R, and Stata. Real-time collaboration, block-level comments, and sharing by link or email make it practical to develop and review work together. The tradeoff is that the Free plan caps editing access at three people, so a larger team will need to budget for the Team plan even if many colleagues only need to view.

Notebook work can extend beyond the editor: analyses can become dashboards or hosted interactive apps using live data, and notebooks can be deployed as APIs. That breadth is useful for teams that want to put analysis in front of colleagues or applications without treating the notebook as the final deliverable.

Execution and integrations

Scheduling supports hourly, daily, weekly, or monthly runs. Built-in connections include PostgreSQL, BigQuery, Amazon S3, MySQL, Snowflake, GitHub, and dbt. Execution is hybrid, and the official extension brings notebook editing, block execution, local execution, and deployment to VS Code, Cursor, Windsurf, and Antigravity. This flexibility suits teams working across hosted and local environments, though the product’s breadth is less compelling if all that is needed is a simple, standalone notebook.

Supported formats include .deepnote, .ipynb, .qmd, .py (Percent/Marimo), and PDF. Deepnote says it holds SOC 2 Type II certification, encrypts data at rest with AES 256-bit encryption and in transit with TLS 1.2 or higher, and does not use customer data to train or improve AI or ML models. It also says it runs regular third-party penetration tests and a private bug bounty program. Technical support for all customers is available through Intercom and email on weekdays from 9 am to 5 pm Pacific Time.

Pricing

Deepnote is freemium, with a 14-day trial and paid access from $39/user/mo (annual). The Free plan costs 0.00 USD per free, billed forever. It allows up to three editors and five projects, with unlimited Basic machines at 5 GB RAM and 2 vCPU, plus seven-day revision history. That is a meaningful way to start a small project, but the editor and project ceilings, short history, and absence of the Team plan’s scheduled notebooks and background execution constrain ongoing team use.

The Team plan costs 3920.00 USD per month, billed per editor/month billed yearly. It includes unlimited viewers and notebooks, premium integrations, background execution, scheduled notebooks, 30-day revision history, $39 worth of AI credits every month, $280 worth of CPU every month, and $50 worth of GPU every month. It is the fit for teams that need shared production workflows and more compute allowances; the annual per-editor billing basis matters for teams sizing seats, even though viewers are unlimited.

Enterprise has custom pricing and adds priority support, a dedicated success manager, SSO and directory sync, audit logs, single-tenancy, and private Docker images. It is aimed at organizations that need those administrative or deployment controls rather than simply more notebook capacity.

Platforms

Deepnote supports web, Linux, macOS, and Windows, as well as self-hosted use, an API, and an editor extension. The mix accommodates both browser-based work and teams that prefer integrating notebook editing into their coding editor.

Who it's for

Deepnote is best suited to data teams that want collaborative notebooks to feed scheduled analysis, dashboards, interactive apps, or APIs, and that value a choice of local and hosted execution. A small group can assess the workflow on Free. Teams that need more than three editors, more projects, scheduled runs, or longer revision history should weigh Team’s per-editor annual billing. It is a weaker fit for individual notebook users who do not need collaboration, deployment, or the paid plan’s workflow features.

Pros and cons

Pros: Notebooks can progress into dashboards, live-data apps, scheduled jobs, or APIs, giving teams several ways to operationalize analysis.
Pros: Real-time collaboration, block comments, and link or email sharing support review across a team.
Pros: The Free plan provides unlimited Basic machines and a useful starting allowance of three editors and five projects.
Cons: Free access is capped at three editors and five projects, and revision history lasts only seven days.
Cons: Team’s $39/user/mo (annual) starting rate makes broader editing access a recurring per-seat decision, despite unlimited viewers.

Alternatives

Choose Datalore instead if its free allowance of 120 CPU S machine hours, 10 GB cloud storage, two parallel notebooks, and one workspace better matches a small cloud-notebook workload. Hex is another freemium option, with a Community plan offering data-source connections, all cell types, small compute, and an agent trial; it may suit readers comparing a free entry point for that set of capabilities.

Google Colab is worth considering for a free notebook option, though its free plan has no guaranteed compute-unit access and limited GPU access; its Colab Pro plan is 8.33 USD per month on an annual/fixed-term plan. Kaggle Notebooks is a free alternative with up to 12-hour CPU/GPU sessions and a 20 GB autosaved disk, but free P100 GPU and TPU v3-8 availability is limited and may queue.

BinderHub is an open-source deployment option for operators prepared to supply their own cloud or hardware and infrastructure. Nextjournal is another freemium notebook option, with unlimited private notebooks on its Free plan alongside limited concurrent compute resources. Observable offers a free plan with few tokens per day, 1 GB monthly file attachments, and watermarked embeds, which may better suit readers focused on that kind of notebook sharing. JupyterLab is free, open-source software that can be installed locally with pip, making it an alternative for users who want a locally installed notebook environment.

For broader comparisons, see Notebook Software, Data Science Platforms, and Coding Playgrounds.

Verdict

Choose Deepnote if your team wants collaborative data notebooks that can move into scheduled workflows, dashboards, apps, and APIs, with both hosted and local execution options. Its free tier makes a small-team start possible, but the five-project and three-editor caps are real constraints; look elsewhere if you need a straightforward individual notebook or cannot justify annual per-editor Team pricing for broader access.

	Deepnote	JupyterHub
Free plan	Yes	Yes
Free trial	Yes	No
Paid from	$3,920/mo	Free
Open source	No	No
Platforms	api, extension, Linux, macOS, self-hosted, Web, Windows	api, Linux, self-hosted, Web
Free plan	Yes	Yes

Deepnote vs JupyterHub

Deepnote

JupyterHub