Best Self Hosted Alternatives to Anaconda Notebooks

JupyterLab is a web-based, extensible interactive computing environment built on the Jupyter architecture. It provides a unified workspace for authoring and running notebooks, editing files, using terminals, and exploring data with rich, interactive outputs.

Key Features

• Multi-document interface combining notebooks, text editor, terminals, file browser, and rich outputs in one workspace
• Extension system for adding UI panels, commands, renderers, and integrations (prebuilt and source extensions)
• Notebook authoring with executable cells, embedded narrative text, and rich visualizations
• Kernel management for running code in different languages via the Jupyter kernel protocol
• Workspaces and customizable UI layout, settings, and keyboard shortcuts
• Real-time collaboration support (when configured with compatible server components)

Use Cases

• Data exploration and visualization workflows for analytics and research
• Reproducible reports and computational narratives shared as notebooks
• Teaching, workshops, and interactive coding environments for teams

Limitations and Considerations

• Advanced capabilities (for example real-time collaboration and multi-user deployments) may require additional configuration and compatible backends such as Jupyter Server/JupyterHub
• JupyterLab 3 has reached end of maintenance; newer deployments should use JupyterLab 4

JupyterLab is a flexible choice for individuals and organizations that need an interactive, browser-based environment for notebooks and code. Its modular architecture and extension ecosystem make it suitable for both lightweight personal use and more customized, integrated deployments.

Livebook is a web application for creating interactive and collaborative notebooks that evaluate Elixir code on demand. Notebooks are stored as .livemd (a Markdown subset) and combine prose, executable cells, and rich output for data visualization and automation. (github.com)

Key Features

• Executable Elixir code cells with sequential evaluation and state tracking (stale cell annotation).
• Rich editor experience (autocompletion, inline docs, formatting) powered by a web code editor integration.
• Interactive visualizations via Kino and supported libraries (Vega-Lite, MapLibre) for charts, tables, and maps.
• Smart cells: high-level, UI-driven cells that generate and run code for common tasks (databases, ML models, plotting).
• Multiple runtimes: launch a fresh Elixir instance, connect to an existing node, or run inside an existing Elixir project with access to its modules and deps.
• Multiple deployment options including a desktop app, Docker images, and running inside platforms such as Hugging Face Spaces for GPU-backed ML workloads. (github.com)

Use Cases

• Teaching and documentation: interactive Elixir tutorials and reproducible technical walkthroughs stored in versionable .livemd files.
• Data exploration and ML prototyping: query databases, visualize data, and run Hugging Face models via Smart cells or deployed Spaces.
• Internal tools and automation: convert notebooks into multi-session Livebook Apps to run shared workflows and lightweight internal UIs. (livebook.dev)

Limitations and Considerations

• Language scope: Livebook is Elixir-centric; capabilities for other languages are limited compared to multi-language notebook platforms.
• Cloud Smart cell caveats: some Smart cell features and integrations (e.g., running models) depend on external services or platform settings (Hugging Face Spaces visibility and secrets), which may affect reproducibility or feature availability in hosted environments. (github.com)

Livebook provides a focused, production-ready notebook experience for Elixir developers and teams that need interactive documentation, data exploration, and workflow automation. Its integrations, runtime flexibility, and collaboration features make it suitable for teaching, prototyping, and building internal apps.

RStudio Server is a web-accessible version of the RStudio IDE for data science development in R and Python. It provides a full coding workbench in the browser, making it easier to centralize compute and enable access for multiple users.

Key Features

• Browser-based IDE experience with console, source editor, plots, workspace, help, and history
• Syntax highlighting, code completion, and smart indentation
• Run code directly from the editor (line, selection, or file)
• Project-based workflow for managing multiple working directories
• Integrated tools for debugging and error diagnosis
• Authoring support for technical documents, including Sweave and TeX
• Package development tooling to support R package workflows

Use Cases

• Centralized data science environment for teams using shared servers or managed infrastructure
• Teaching and training environments where learners access a consistent IDE via a browser
• Remote development when local installation is not desired or practical

RStudio Server is a mature, widely used IDE option for organizations standardizing R/Python workflows and offering a consistent development experience across users and machines.