Exploring Sisense, Project Jupyter & Visivo
Sisense vs. Project Jupyter vs. Visivo
Compare key features, capabilities, and differentiators between Sisense, Project Jupyter, 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 | Sisense | Project Jupyter | Visivo |
|---|---|---|---|
| Deployment Model | Windows/Linux on-prem, Sisense Cloud (managed), Private cloud | Open-source (local), Jupyter server, JupyterHub deployment | Open-source, Cloud Service, Self-hosted |
| Pricing | Commercial (Proprietary). Pricing by seat and consumption. | Free (BSD license) | 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.
Sisense
Project Jupyter
Visivo
Ease of Development & Deployment
Development experience directly impacts team productivity and time-to-value.
Sisense
Project Jupyter
Visivo
Key Integrations & Ecosystem
A robust ecosystem of integrations is essential for modern BI tools.
Sisense
Project Jupyter
Visivo
Visualization Capabilities
The ability to create compelling visualizations is key to data storytelling.
Sisense
Two flavors merged: traditional dashboard builder (drag-drop charts, with advanced widget for custom UI via scripting) and a notebook-style interface (from acquired Periscope Data) for SQL/Python. Visualizations include a wide range of widgets and the special Sisense BloX for custom coded infographic-like blocks. Highly customizable via JavaScript (for those inclined).
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).
Visivo
Highly custom UI with easy defaults
Detailed Differentiators
Each platform's unique strengths and limitations.
Sisense
Project Jupyter
Visivo
Security & Architecture
Critical considerations for enterprise deployments.
Sisense
DB Access: Depending on setup – Live mode: Sisense queries your DB on the fly (needs access); Elasticube mode: data is extracted into Sisense's proprietary in-memory cube (so queries don't hit source DB at runtime). Virtualization: Allows combining multiple sources in one view via its cubes (not exactly virtualization, more like federation into a single cache). Push: In Elasticube mode, data is essentially pushed into Sisense's storage on a refresh schedule. Other: Robust security – single sign-on, row-level security in Elasticubes, and extensive admin controls.
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.
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
