The Jupyter Notebook vs. Deepnote
A side-by-side comparison based on G2 review data.
| Metric | The Jupyter Notebook | Deepnote |
|---|---|---|
| Overall rating | 4.6 | 4.5 |
| Review count | 255 | 387 |
| Ease of use | 9.2 | 9.0 |
| Ease of setup | 9.3 | 9.1 |
| Quality of support | 8.6 | 8.9 |
| Meets requirements | 9.1 | 8.8 |
| NPS | 76.25 | 70.75718 |
| Small Business | 34.4% | 67.7% |
| Mid-Market | 30.0% | 25.0% |
| Enterprise | 35.6% | 7.3% |
| Total page views | 232 | 631 |
| Total LLM citations | 490 | 5,340 |
The Jupyter Notebook
Jupyter Notebook is an open-source, web-based interactive computing environment that enables users to create and share documents containing live code, equations, visualizations, and narrative text. It supports over 40 programming languages, including Python, R, Julia, and Scala, making it a versatile tool for data science, scientific computing, and machine learning. Key Features: - Interactive Computing: Allows real-time code execution and immediate feedback, facilitating an interactive development process.
- Ease of Use
- Data Visualization
- Useful
- Data Analysis
- Performance
- Feature Variety
Deepnote
Deepnote is a data workspace where agents and humans work together. It's designed to simplify data exploration, accelerate analysis, and quickly deliver actionable insights for you and your team. Unlike outdated tools such as Jupyter, Deepnote is built with the next decade in mind. Deepnote gives anyone working with data superpowers. It unifies your data workflow through an integrated semantic layer, preparing your data for advanced AI applications.
- Ease of Use
- Collaboration
- Team Collaboration
- Easy Integrations
- Data Management
- Integrations