Deepnote

Overview

Deepnote is a notebook-centered workspace for data analysis, exploration, and machine learning. It is best suited to data teams that want to collaborate on analyses and carry them into scheduled jobs, APIs, dashboards, or live-data apps. Its breadth is useful, but the free tier’s editor and project caps make it a limited starting point for a growing team.

Made by a company founded in 2019 and headquartered in Prague, Deepnote supports Python, SQL, R, and Stata. Its hybrid execution model and support for.deepnote,.ipynb,.qmd,.py (Percent/Marimo), and PDF formats give it room to fit different notebook workflows. It belongs among Notebook Software, Data Science Platforms, and Coding Playgrounds.

Key features

Notebook work and AI

The AI data copilot can chat with data, create charts, and write code. That puts assistance close to analysis rather than separating it into a general-purpose chat tool. Notebooks can also become dashboards or apps, making it easier to present results in a form colleagues can use beyond the coding workspace.

Collaboration and sharing

Real-time collaborative notebooks, comments on individual blocks, and sharing by link or email invitation support review as work develops. This is a practical advantage for teams refining an analysis together, though the Free plan allows only three editors.

Apps, automation, and integrations

Users can host interactive apps backed by live data, turn analyses into team dashboards, schedule notebooks hourly, daily, weekly, or monthly, and deploy notebooks as APIs. Those options make Deepnote more than a place to explore data: it can also serve as a route from analysis to recurring work or a usable data product. Built-in integrations include PostgreSQL, BigQuery, Amazon S3, MySQL, Snowflake, GitHub, and dbt.

Editor extension and security

The official extension supports VS Code, Cursor, Windsurf, and Antigravity, with notebook editing, block execution, local execution, and deployment to Deepnote.com. It suits developers who prefer those editors while retaining a path to Deepnote’s hosted environment. Deepnote says it has SOC 2 Type II certification, conducts regular third-party penetration testing, and runs a private bug bounty program. It encrypts data at rest with AES 256-bit encryption and data in transit with TLS 1.2 or higher, and says customer data is not used to train, fine-tune, or otherwise improve AI or ML models.

Pricing

Deepnote is freemium, with a 14-day trial and paid access starting at $39/user/mo (annual). The price and caps make the choice between plans consequential: free is useful for an individual or small group evaluating notebook workflows, while recurring team execution and broader collaboration push toward paid service.

PlanPriceWhat it includesBest fitFreefree (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.Individuals and small groups whose projects fit the editor and project limits. The short revision history and capped collaboration leave less room for larger teams.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.Teams that need scheduled or background work, premium integrations, longer history, and monthly compute and AI credits. The per-editor annual billing is a commitment to account for as a team grows.EnterpriseCustom pricingPriority support, a dedicated success manager, SSO and directory sync, audit logs, single-tenancy, and private Docker images.Organizations that need identity controls, auditability, single-tenancy, or dedicated support.All customers receive technical support through Intercom and email on weekdays from 9 am to 5 pm Pacific Time at minimum. GPU compute is supported, but the Team plan’s included GPU value is finite; teams with heavier workloads should weigh that allowance alongside the per-editor cost.

Platforms

Deepnote lists web, Linux, macOS, Windows, self-hosted, API, and extension platforms. The editor extension supports VS Code, Cursor, Windsurf, and Antigravity; local execution is available alongside deployment to Deepnote.com. That mix suits teams with varied development environments, although the platform list alone does not establish that every feature is available in every mode.

Who it's for

Deepnote is a strong fit for data professionals and teams that want a shared notebook environment with a path from exploration to scheduled output, APIs, and interactive apps. It is especially relevant where Python, SQL, R, or Stata work benefits from live collaboration and integrated data connections. A solo user can start free, but teams that need more than three editors, five projects, or seven days of revision history will outgrow Free’s explicit limits. It is a weaker fit for buyers who only need a local notebook environment or who do not need the collaboration and publishing layer.

Pros and cons

Pros: Analysis can progress into scheduled notebooks, APIs, dashboards, and live-data apps, avoiding a hard divide between exploration and sharing.

Pros: Real-time collaboration, block comments, and link or email sharing support team review within the notebook workflow.

Pros: The editor extension brings notebook editing and execution to several popular coding editors, including local execution.

Pros: A wide selection of listed integrations covers databases, cloud storage, GitHub, and dbt.

Cons: Free is tightly bounded for teams: three editors, five projects, and only seven days of revision history.

Cons: Team pricing is per editor and billed yearly, so costs scale with the number of editors even though viewers are unlimited.

Cons: The Team plan’s AI, CPU, and GPU amounts are monthly allowances, which may constrain teams with sustained heavier use.

Alternatives

Choose Paperspace Gradient if a freemium coding-playground option with a free individual plan and 5GB storage better matches the need; its free instances can also incur utilization costs. Choose KNIME Analytics Platform if free, open-source software for Linux, macOS, or Windows is the priority. Choose Datalore if its Cloud Free allowance of 120 CPU S machine hours, 10 GB cloud storage, two parallel notebooks, and one workspace fits a small cloud workflow.

ML Workspace is another free option for a single-user development environment, provided Docker and its system requirements fit. NETVIBES may suit readers considering an enterprise data science offering. Choose Hex if its Community plan’s data-source connections, cell types, small compute, and agent trial align better with the intended workflow. MLJAR Studio is a freemium alternative with a free allowance of 50 prompts per month and 10 published conversations. Amazon SageMaker Autopilot is an alternative for buyers considering a pay-as-you-go service rather than a free-plan notebook workspace.

Verdict

Deepnote is a compelling choice for data teams that want notebooks to remain collaborative while also becoming scheduled jobs, APIs, dashboards, and live-data apps. Its integrations, editor extension, and support for several notebook formats make it flexible across established workflows. The main reason to look elsewhere is scale or simplicity: the free tier has narrow team limits, Team is billed per editor yearly, and buyers who need only a standalone notebook environment may not benefit from its broader collaboration and publishing layer.