Bokeh vs Plotly

Side-by-side — pricing, strengths, tradeoffs, and fit.

Bokeh

Interactive Web Plotting for Python.

Plotly

Collaborative web plotting for Python and matplotlib.

At a glance

Open SourceFree Tier
● Established·From $0
Open SourceFree Tier
· Not enough data·From Freemium

Overview

One-liner

Interactive Web Plotting for Python.

One-liner

Collaborative web plotting for Python and matplotlib.

Maturity

Established

Maturity

Not enough data

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Starts at

$0

Starts at

Freemium

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Projects requiring high-performance interactivity over large datasets
Web applications that need to visualize streaming data
Developers who want to create interactive plots and charts for web apps without a backend service

✓ Best for

Teams needing to create and share interactive data visualizations in Python
Projects requiring high-quality, web-based graphing capabilities
Collaborative environments where multiple users need to interact with the same plots

Not ideal for

✕ Not for

Teams needing real-time streaming (Bokeh is more suited for batch processing)
Projects with strict performance constraints where JavaScript libraries might be lighter-weight options

✕ Not for

Real-time streaming applications (Plotly is not designed for real-time updates)
Applications that require extremely lightweight plotting solutions

Strengths

↑ Strengths

Interactive plots and charts for web applications
High-performance interactivity over large datasets
Supports streaming data visualization
Customizable visualizations with extensive styling options

↑ Strengths

Interactive charts and graphs
Collaborative web-based platform
Support for over 20 languages
High-quality data visualization capabilities

Weaknesses

↓ Weaknesses

Limited third-party integration support
Performance issues with very large datasets

↓ Weaknesses

Limited offline support and documentation for advanced features
Performance issues with large datasets
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