Best Data Science Notebooks in 2025

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Key Jupyter features:

Interactive Computing Rich Media Output Language Agnostic Collaborative Features

Interactive code examples/posts.

Key Observable features:

Collaborative Environment Reactive Programming Built-in Data Visualization Libraries Notebook Interface

Open Source

Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

Key Algorithmia features:

Wide Range of Algorithms Scalability Ease of Integration Supports Multiple Languages

Open Source

Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

Key neptune.ai features:

Experiment Tracking Collaboration Features Integration Capability Interactive Dashboard

Open Source freemium

RunKit notebooks are interactive javascript playgrounds connected to a complete node environment right in your browser. Every npm module pre-installed.

Key RunKit features:

Ease of Use Immediate Feedback Installation-free Package Integration

Machine Learning Operationalization.

Key MCenter features:

Variety of Services Advanced Technology Professional Staff Patient Comfort

Open Source Polyglot Data Science Tool.

Key BeakerX features:

Polyglot Environment Interactive Widgets Enhanced Table Display Extensibility

Open Source

A collaboration platform for data scientists.

Key Deepnote features:

Collaborative Features Integration with Popular Tools User-Friendly Interface Cloud-Based

Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.

Key Managed MLflow features:

Scalability Ease of Use Integration Security

Developer tools for deep learning research.

Key Weights & Biases features:

Experiment Tracking Collaboration Features Integration Capability Hyperparameter Tuning

nteract is a desktop application that allows you to develop rich documents that contain prose...

Key nteract features:

Ease of Use Interactivity Multi-language Support Open Source

Open Source

Iterative removes friction from managing datasets and ML models and introduces seamless data scientists collaboration.

Key Iterative.ai features:

Version Control with DVC Integration with Existing Tools Scalability Open Source

The open-source, web-based thinking tool that facilitates effective thinking for solving problems.

Key Calculist features:

User-Friendly Interface Flexible Structure Cross-Platform Availability Real-Time Collaboration

Open Source freemium $4.0 / Monthly