Jupyter vs Grafana

The notebook that made data scientists feel like artists, until they tried to version control it meets the dashboard wizard that turns your metrics into beautiful, actionable art—if you can survive the panel configuration maze. Here's our take.

Jupyter

Nice Pick

The notebook that made data scientists feel like artists, until they tried to version control it.

Pros

• Interactive notebooks perfect for exploratory data analysis and teaching
• Supports over 40 languages, making it versatile for multi-language projects
• Rich output with live code, visualizations, and markdown in one document

Cons

• Notoriously messy for version control and collaboration due to JSON-based files
• Can become sluggish with large datasets or complex visualizations

Grafana

The dashboard wizard that turns your metrics into beautiful, actionable art—if you can survive the panel configuration maze.

Pros

• Unmatched flexibility for visualizing time-series data from any source
• Vast plugin ecosystem for integrations with tools like Prometheus and Elasticsearch
• Real-time alerting that actually works without breaking the bank

Cons

• Steep learning curve for custom panels and complex queries
• Can get sluggish with too many dashboards or heavy data loads

The Verdict

Use Jupyter if: You want interactive notebooks perfect for exploratory data analysis and teaching and can live with notoriously messy for version control and collaboration due to json-based files.

Use Grafana if: You prioritize unmatched flexibility for visualizing time-series data from any source over what Jupyter offers.

The Bottom Line

Jupyter wins

The notebook that made data scientists feel like artists, until they tried to version control it.