bqplot vs Bokeh
Side-by-side — pricing, strengths, tradeoffs, and fit.
bqplot
Interactive plotting API for Jupyter notebooks.
Bokeh
Interactive Web Plotting for Python.
At a glance
Open SourceFree Tier
● Established·From $0
Open SourceFree Tier
● Established·From $0
Overview
One-liner
One-liner
Interactive plotting API for Jupyter notebooks.
One-liner
Interactive Web Plotting for Python.
Maturity
Maturity
EstablishedMaturity
EstablishedOpen source
Open source
✓ YesOpen source
✓ YesPricing
Free tier
Free tier
✓ AvailableOpen source — free to use
Free tier
✓ AvailableOpen source — free to use
Starts at
Starts at
$0
Starts at
$0
Model
Model
Flat rate
Model
Flat rate
Enterprise
Enterprise
✕ NoneEnterprise
✕ NoneBest for
✓ Best for
Data scientists who need interactive plots within their Jupyter workflows
Python developers working on projects that require complex visualizations in notebooks
✓ 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
Not ideal for
✕ Not for
Projects requiring real-time data streaming visualization outside of Jupyter environments
Users looking for a web-based platform for creating and sharing plots without coding
✕ 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
Strengths
↑ Strengths
Interactive plots for Jupyter notebooks
Supports complex visualizations with a high-level API
Customizable and extensible plot types
↑ Strengths
Interactive plots and charts for web applications
High-performance interactivity over large datasets
Supports streaming data visualization
Customizable visualizations with extensive styling options
Weaknesses
↓ Weaknesses
Limited third-party integration support
Performance issues with large datasets
Sparse community and limited documentation
↓ Weaknesses
Limited third-party integration support
Performance issues with very large datasets