Exploring Project Jupyter, Plotly Dash & Visivo
Project Jupyter vs. Plotly Dash vs. Visivo
Compare key features, capabilities, and differentiators between Project Jupyter, Plotly Dash, Visivo. This comprehensive analysis will help you make an informed decision for your data visualization needs.
Quick Comparison
Key features and capabilities at a glance
| Feature | Project Jupyter | Plotly Dash | Visivo |
|---|---|---|---|
| Deployment Model | Open-source (local), Jupyter server, JupyterHub deployment | Self-hosted (open-source) or Plotly Enterprise Server | Open-source, Cloud Service, Self-hosted |
| Pricing | Free (BSD license) | Open-source (MIT); Enterprise plans for support | Open source (GPL-3.0) |
| Cost | $ | $ | $ |
| Git Integration | |||
| CI/CD & Testing | |||
| Real-time | |||
| AI Features | |||
| Visual to Code | |||
| DAG-Based |
Target Users & Use-Cases
Each BI tool is designed with specific user personas in mind.
Project Jupyter
Plotly Dash
Visivo
Ease of Development & Deployment
Development experience directly impacts team productivity and time-to-value.
Project Jupyter
Plotly Dash
Visivo
Key Integrations & Ecosystem
A robust ecosystem of integrations is essential for modern BI tools.
Project Jupyter
Plotly Dash
Visivo
Visualization Capabilities
The ability to create compelling visualizations is key to data storytelling.
Project Jupyter
Not a conventional BI tool – it's a computing environment. Visuals come from libraries (Matplotlib, Plotly, etc.) within code cells. Highly flexible outputs (any HTML/JS). Sharing typically static (not interactive unless using Voila or similar to create dashboards).
Plotly Dash
Fully custom UI with code; any plotly or HTML component; highly flexible but code-driven
Visivo
Highly custom UI with easy defaults
Detailed Differentiators
Each platform's unique strengths and limitations.
Project Jupyter
Plotly Dash
Visivo
Security & Architecture
Critical considerations for enterprise deployments.
Project Jupyter
DB Access: If a notebook connects to a DB, it does so directly (with credentials in code or config). Virtualization: No – but you could use tools like Trino via Python to virtualize in code. Push: No, unless custom code to push data. Other: Jupyter itself has no auth (except if behind JupyterHub). Security concerns if sharing notebooks with sensitive data output.
Plotly Dash
Requires direct DB/API access in code (no built-in data layer); no built-in virtualization or push. App pulls data as coded; security handled by app deployment (auth, etc. configurable)
Visivo
No db access required. Very strong security features due to the DAG-based access controls and the push based deployment model.
Why Visivo Stands Out
While each platform has its strengths, Visivo offers unique advantages for modern data teams.
Ready to Experience Modern BI?
Try Visivo today and see how it transforms your data analytics workflow.
$ curl -fsSL https://visivo.sh | bash
