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Open-source alternatives to Databricks Notebooks

Compare community-driven replacements for Databricks Notebooks in notebook & data science platforms workflows. We curate active, self-hostable options with transparent licensing so you can evaluate the right fit quickly.

Databricks Notebooks logo

Databricks Notebooks

Databricks Notebooks enable teams to coauthor notebooks with versioning and built-in visualizations, streamlining data science and ML workflows.Read more
Notebook & Data Science Platforms
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Key stats

  • 7Alternatives
  • 6Active development

    Recent commits in the last 6 months

  • 5Permissive licenses

    MIT, Apache, and similar licenses

Counts reflect projects currently indexed as alternatives to Databricks Notebooks.

All open-source alternatives

JupyterHub logo

JupyterHub

Scalable multi-user hub for Jupyter notebooks

Active developmentPermissive licenseFast to deployPython

Why teams choose it

  • Central Hub with Tornado server and configurable HTTP proxy
  • Pluggable authenticators (PAM, OAuth, LDAP, Kerberos)
  • Multiple spawners: local, Docker, Kubernetes, batch systems

Watch for

Default PAM authentication requires privileged setup

Migration highlight

Classroom notebook server

Students log in with university credentials and receive isolated notebook instances for assignments.

Jupytext logo

Jupytext

Edit Jupyter notebooks as plain text scripts for seamless version control

Active developmentPermissive licenseIntegration-friendlyPython

Why teams choose it

  • Convert notebooks to .py, .md, .R, .jl and other script formats
  • Paired notebook synchronization between .ipynb and script files
  • Command‑line interface for batch conversion, syncing, and piping

Watch for

Notebook outputs are not stored in text formats

Migration highlight

Version‑controlled notebooks in Git

Store .py versions in Git, get clean diffs, and regenerate .ipynb outputs locally.

Polynote logo

Polynote

Polyglot notebook with IDE‑grade editing for Scala, Python, SQL

Active developmentPermissive licenseFast to deployJupyter Notebook

Why teams choose it

  • IDE‑grade code editing with autocomplete and parameter hints
  • WYSIWYG text cells with TeX equation support
  • Seamless multi‑language notebooks sharing definitions across Scala, Python, SQL, Vega

Watch for

Experimental project may lack long‑term stability

Migration highlight

Exploratory data analysis with Scala and Spark

Combine Scala's type safety with Spark's distributed processing in an interactive notebook.

Elyra logo

Elyra

AI‑focused extensions that turn JupyterLab into a pipeline hub

Active developmentPermissive licenseFast to deployPython

Why teams choose it

  • Visual Pipeline Editor for drag‑and‑drop workflow design
  • Hybrid runtime execution via Jupyter Enterprise Gateway
  • Integrated (experimental) debugger for Python scripts

Watch for

Debugger is marked experimental and may be unstable

Migration highlight

Create and run end‑to‑end ML pipelines

Design visual pipelines, connect notebook steps, and execute them on remote clusters with a single click.

JupyterLab logo

JupyterLab

Next-generation interactive computing environment for notebooks, code, and data

Active developmentFast to deployIntegration-friendlyTypeScript

Why teams choose it

  • Modular UI with drag‑and‑drop layout for notebooks, terminals, and editors
  • Rich extension ecosystem via npm, PyPI, and conda
  • Native support for modern browsers (Firefox, Chrome, Safari)

Watch for

Requires Python environment setup

Migration highlight

Exploratory data analysis

Run notebooks, visualize results, and edit scripts side‑by‑side for faster insight generation.

marimo logo

marimo

Reactive Python notebooks that stay reproducible, git‑friendly, and deployable

Active developmentPermissive licenseIntegration-friendlyPython

Why teams choose it

  • Reactive execution automatically updates dependent cells
  • Pure Python notebooks are git‑friendly and script‑runnable
  • Built‑in UI widgets and AI‑assisted cell generation

Watch for

Learning curve for the reactive model

Migration highlight

Exploratory data analysis with live filters

Analysts adjust sliders and instantly see updated visualizations, keeping results consistent and reproducible.

Pretzel logo

Pretzel

AI‑enhanced Jupyter alternative with seamless code assistance

Fast to deployAI-powered workflowsTypeScript

Why teams choose it

  • Integrated AI code generation and editing directly in notebook cells
  • Inline tab completion with variable and function suggestions
  • AI sidebar for chat, code search, and on‑demand generation

Watch for

AI features depend on external model APIs, which may incur costs

Migration highlight

Rapid prototype generation

Generate boilerplate functions or visualizations in seconds using the AI prompt, reducing initial coding time.

Choosing a notebook & data science platforms alternative

Teams replacing Databricks Notebooks in notebook & data science platforms workflows typically weigh self-hosting needs, integration coverage, and licensing obligations.

  • 6 options are actively maintained with recent commits.

Tip: shortlist one hosted and one self-hosted option so stakeholders can compare trade-offs before migrating away from Databricks Notebooks.