Deepnote

Deepnote is a notebook-centered workspace for analysis, exploration, and machine learning. It suits data professionals who need to develop work with colleagues and share it as a dashboard, app, or API. Its breadth is compelling, but the free plan’s project and history caps and the Team plan’s annual per-editor price deserve close attention.

Overview

Deepnote brings coding, data work, and collaboration into one workspace, with Python, SQL, R, and Stata support and a hybrid execution model. Notebook files can use .deepnote, .ipynb, .qmd, .py (Percent/Marimo), or PDF formats, giving teams several ways to work with and distribute their notebooks.

Made by a company founded in 2019 and headquartered in Prague, Deepnote is offered on a freemium basis. It supports web, Linux, macOS, Windows, self-hosted deployments, an API, and an editor extension. The extension works with VS Code, Cursor, Windsurf, and Antigravity for notebook editing, block execution, local execution, and deployment to Deepnote.com.

Deepnote belongs among Notebook Software, Data Science Platforms, and Coding Playgrounds. Its mix of notebooks and shareable data products makes it broader than a place simply to write and run code.

Key features

AI and notebook outputs

The AI data copilot can chat with data, create charts, and write code. This can help move from questions to visual results within a notebook, while the option to turn notebooks into dashboards or apps gives teams a way to present analysis beyond its working form.

Collaboration and data apps

Real-time collaborative notebooks, block-level comments, and sharing by link or email invitation support joint work and review. Users can host interactive apps with live data and make dashboards for their team; that is useful when an analysis needs to remain an active, accessible product rather than a static handoff.

Scheduling, deployment, and integrations

Notebooks can run on hourly, daily, weekly, or monthly schedules, and can be deployed as APIs. Built-in integrations include PostgreSQL, BigQuery, Amazon S3, MySQL, Snowflake, GitHub, and dbt. Together, these features suit recurring data workflows, though the Team plan is required for scheduled notebooks and background execution.

Security and support

Deepnote says it holds SOC 2 Type II certification, conducts regular third-party penetration testing, and runs a private bug bounty program. It describes encryption at rest as AES 256-bit and encryption in transit as TLS 1.2 or higher, and says customer data is not used to train or improve AI or ML models. All customers receive technical support through Intercom and email on weekdays from 9 am to 5 pm Pacific Time as a minimum.

Pricing

Deepnote has a free plan, a 14-day trial, and paid access from $39/user/mo (annual). The plans differ not only in price but in the room they give teams to collaborate and retain project history.

Plan	Price	What it includes
Free	free (billed forever)	Up to 3 editors, up to 5 projects, unlimited Basic machines with 5 GB RAM and 2 vCPU, and 7 day revision history.
Team	$3,920 a month (billed per editor/month billed yearly)	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.
Enterprise	Custom pricing	Priority support, a dedicated success manager, SSO and directory sync, audit logs, single-tenancy, and private Docker images.

The Free plan is a useful way for an individual or small group to start, but three editors and five projects can constrain a growing team, and a week of revision history leaves less room to revisit earlier work. Team removes those project and notebook limits and extends history to 30 days, while adding scheduling and monthly compute and AI credits. Its annual per-editor billing makes it a more considered commitment than the free tier. Enterprise is the fit for organizations that need identity controls, audit logs, or single-tenancy.

Platforms

Deepnote spans web, Linux, macOS, Windows, self-hosted use, an API, and an editor extension. Local execution in the extension offers an alternative to running every notebook in Deepnote, while deployment to Deepnote.com connects editor-based work back to the hosted workspace.

Who it's for

Deepnote is a strong match for data professionals and teams that want notebooks to feed into shared dashboards, live-data apps, or scheduled workflows. The free plan suits evaluation and small projects; teams needing more editors, projects, history, or recurring background work should weigh the Team plan. It is less suitable for a team that cannot justify annual per-editor billing or needs more free-plan capacity.

Pros and cons

• Pro: Notebooks can become dashboards, live-data apps, or APIs, giving teams multiple ways to put analysis to use.
• Pro: Real-time collaboration, block comments, and link or email sharing support shared development and review.
• Pro: The editor extension supports local execution as well as deployment to Deepnote.com across four named coding editors.
• Con: The free plan caps teams at three editors and five projects, with only seven days of revision history.
• Con: Scheduled notebooks and background execution are Team features, so recurring workflows require a paid plan.
• Con: Team is billed per editor monthly on an annual basis, which may be a poor fit for teams seeking flexible short-term costs.

Alternatives

• Datalore is worth considering for a free cloud start: its Cloud Free plan includes 120 CPU S machine hours, 10 GB cloud storage, two notebooks in parallel, and one workspace.
• JupyterLab is the clearer choice for people who want free, open-source notebook software installed locally with pip.
• Hex offers another freemium option, with a Community plan that connects to any data source and includes all cell types, small compute, and an agent trial.
• Nextjournal may suit users prioritizing unlimited private notebooks and data and secrets management on its free plan.
• Google Colab is an alternative for users willing to work with limited GPU access and no guaranteed access to compute units on its free plan.
• Observable offers a free plan with a daily token allowance, 1 GB monthly file attachments, and embeds with a watermark.
• Kaggle Notebooks is a free option for users who can work within session limits and the possibility of queues for limited P100 GPU and TPU availability.
• Pluto.jl is another free alternative.

Verdict

Choose Deepnote if your data work needs to move from collaborative notebooks into maintained dashboards, live-data apps, or scheduled and deployed workflows. Its strongest case is the continuity between analysis and sharing; its main drawback is that modest free-plan caps and annual per-editor Team billing can make that continuity costly as a team grows.