Anaconda Notebooks

Anaconda Notebooks provides JupyterLab in a cloud environment for writing, editing, and running Python code through an Anaconda Cloud account. Learners and data science users can start projects from a browser, using packages and computing resources supplied by the service rather than installing Python locally. Two preconfigured environments are available: one with the latest Anaconda Distribution packages and another with packages selected for AI workflows. A notebook can be shared by URL so others can open a copy, work on it with an Anaconda account, or download it. Notebook outputs can also be deployed as web applications with Panel and shared through a URL. Anaconda Assistant for Python can analyze tables and suggest ways to work with the data; Data Connectors save CSV files on Anaconda Cloud for access from Excel or a notebook. The Free plan costs nothing and includes 5 GB of cloud storage. Starter costs $15 a month, billed monthly, with 10 GB per user. Organizations can disable notebook sharing, which can result in a 403 error when a user tries to share.

Anaconda Notebooks combines browser-based JupyterLab with prepared environments and options to share notebooks or deploy outputs. The free plan offers 5 GB of storage; organizations may restrict notebook sharing.

It suits learners and Python or data science users who want to work in JupyterLab from a browser. Teams can use notebook links and Panel deployments to share work, subject to organization sharing settings.

Anaconda Notebooks is a cloud workspace for Python development, aimed at learners and data-science practitioners who want to work in JupyterLab without setting up Python locally. Its strongest case is a browser-based notebook workflow paired with prepared environments and ways to share or publish work; storage caps and organization controls are the main trade-offs.

Overview

With an Anaconda Cloud account, users can write, edit and run Python in JupyterLab, with packages and computing power supplied by the service. That sidesteps setup differences among operating systems and laptops, which is useful for learners and teams that want a common starting point. The corresponding limitation is dependence on a cloud workspace rather than a local installation.

Notebook URLs can let others open a copy, work with it using an Anaconda account or download it. Organizations can disable sharing, in which case an attempted share may return a 403 error. Anaconda says stored data is encrypted at disk and database levels, while application, database, webhook and API traffic uses TLS/HTTPS.

Key features

Prepared Python environments

Two preconfigured environments cover the latest Anaconda Distribution packages and a selection aimed at AI workflows. Environment management, lockfile support, package publishing and private registries extend the offering beyond a basic hosted notebook. This structure gives users a ready foundation, though the available environment choices are described as two presets rather than an open-ended menu of configurations.

Sharing and publishing

Notebook sharing supports collaboration around a copy, while Panel can turn notebook outputs into a web application with a shareable URL. The distinction is useful: collaborators can work from a notebook, while audiences can access a published output. Sharing is not guaranteed in managed organizations, since administrators can prohibit it.

Assistant and data access

Anaconda Assistant for Python can analyze tables and recommend ways to work with data. Data Connectors let users save CSV files on Anaconda Cloud for use from Excel or a notebook. The Anaconda Cloud account handles API key generation and access-based permissions for the AI Assistant, an account-centered approach to controlling that access.

Pricing

The Free plan costs nothing and includes 5 GB of cloud storage. Anaconda Core Free also includes notebooks, thousands of data science, machine-learning and AI packages, Assistant code help and introductory courses. It is a sensible way for individual learners to start, but the 5 GB cap can constrain projects that accumulate data or notebooks.

Starter costs $15 a month, billed monthly, with 10 GB of storage per user. Anaconda Core Starter specifies $15 /user/mo and adds a professional development environment, on-demand training courses and team workspace controls. It suits users who need more storage and a structured workspace, but does not include the security and governance features reserved for Business.

Business costs $50 a month, billed monthly; Anaconda Core Business specifies $50 /user/mo. It adds automated vulnerability scanning, audit trails and project governance, centralized access management and SSO, threat intelligence and curated security data. Those controls make it the relevant tier for organizations with governance needs, rather than a necessary upgrade for every notebook user.

Custom pricing is available for self-hosting on-premises or in private or public cloud, with advanced multi-team governance, custom integrations and SLAs; the Custom plan also describes AI orchestration with built-in observability. This is the enterprise-oriented option for teams needing deployment and governance flexibility rather than a published per-user tier.

Platforms

The notebook workspace runs on the web, with cross-platform support. That favors people who want browser access and to avoid local Python installation; it is not a substitute for a locally installed workflow when browser-based work is unsuitable.

Who it's for

Choose Anaconda Notebooks if you are learning Python, building data-science or AI projects, or collaborating around notebooks and want managed environments without local setup. Teams can benefit from workspace controls and higher-tier governance. Look elsewhere if you need more than the free storage allowance without paying, or if organizational sharing restrictions conflict with your workflow.

Pros and cons

• Pro: Browser-based JupyterLab with packages and computing power provided by the service avoids local Python setup.
• Pro: Two prepared environments, notebook sharing and Panel publishing cover both development and sharing outputs.
• Pro: Business includes concrete security and governance controls, including SSO and audit trails.
• Con: Free storage is limited to 5 GB; Starter raises it to 10 GB per user at $15 a month.
• Con: Organizations may prohibit notebook sharing, limiting a central collaboration feature.
• Con: The web-first model may not suit users who require a local installation.

Alternatives

For another freemium platform, ActiveState Platform has a free organization plan limited to public projects and a paid enterprise offering with custom pricing. Choose Hatch if a free, MIT-licensed Python project manager for Linux, macOS or Windows fits better than a hosted notebook. pip is a free option for users who want a Python package installer on those desktop platforms rather than Anaconda's browser workspace.

pip-tools offers free command-line tools installed per virtual environment and requires Python 3.9 or later. Pixi is a free alternative for Linux, macOS and Windows, with a free prefix.dev package-hosting plan. Twine is a free option for Python 3.10 or later on those platforms. uv and conda-lock are also free alternatives for Linux, macOS and Windows.

The Data Science Platforms list is a useful place to compare broader platform choices. Readers focused on package management can browse Python Package Managers, Artifact repository software or Coding Playgrounds.

Verdict

Anaconda Notebooks is a strong fit for learners and Python or data-science teams who want JupyterLab, prepared environments and notebook-to-web publishing without local setup. The free tier makes it approachable, and Business has meaningful governance controls for organizations. Choose another workflow if 5 GB is too restrictive, you need local-first development, or your organization blocks sharing.