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Head-to-head · Data Visualization Libraries Software

Plotly vs Bokeh

  • Updated Oct 2026
  • Both researched from official sources
  • 1 check side by side
Higher score Plotly #1 in Data Visualization Libraries Software 9.3/10 Free plan Free plan Visit Plotly
Bokeh #6 in Data Visualization Libraries Software 8.6/10 Free plan Free plan Visit Bokeh

Plotly leads on 0 checks, Bokeh on 0, and 1 is even. Who comes out ahead on the 1 yes/no, price and count check where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scorePlotly · 9.3/10
  • Free planboth

Plotly scores higher on our rubric for data visualization libraries software: 9.3 against 8.6 out of 10; our editors rank them #1 and #6.

Plotly is the better fit for teams needing versatile interactive charts and maps. Bokeh is the better fit for python developers building interactive web plots.

  • Plotly fits best

    Teams needing versatile interactive charts and maps

  • Bokeh fits best

    Python developers building interactive web plots

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Side by side

Feature Plotly 9.3/10 Visit ↗ Bokeh 8.6/10 Visit ↗
At a glance
Editor score 9.3 8.6
Ranking #1 in Data Visualization Libraries Software #6 in Data Visualization Libraries Software
Best for Teams needing versatile interactive charts and maps Python developers building interactive web plots
Pricing model Free plan + paid Free
Starting price $290/seat/yr Free plan
Free plan ✓ ✓
Free trial — —
Deployment Cloud, Self-hosted, Desktop Self-hosted
Platforms Web, Windows, macOS Web
Support Tickets, Docs, Email Community, Docs
Integrations 20 integrations 8 integrations
Built for Solo, Small business, Mid-market, Enterprise Solo, Small business, Mid-market, Enterprise
Specs
Supported frameworks Not checked yet Not checked yet
Chart types Not checked yet Not checked yet
Rendering modes Not checked yet Not checked yet
Interactive features Not checked yet Not checked yet
Export formats Not checked yet Not checked yet
License model Not checked yet Not checked yet
Our review
Pros
  • 70+ chart and trace types with rich interactive controls
  • Open-source libraries plus cloud and self-hosted deployment
  • Connects with notebooks, databases, Dash, and Streamlit
  • Offers pan, zoom, hover, tap, and selection tools for interactive plots
  • Supports standalone HTML, embeddable components, and Bokeh server apps
  • Works with Jupyter and a range of Python data sources
Cons
  • The suite spans several products rather than one packaged application
  • Library-first workflows require Python or JavaScript development
  • Pro pricing is per creator seat, with viewers limited to 10
  • Its workflow centers on Python rather than general JavaScript charting
  • Server applications require self-hosted deployment
  • Support is through community resources and documentation
Our verdict

Plotly is an open-source suite for building interactive charts, maps, scientific visualizations, financial graphics, dashboards, and data applications. Its Python and JavaScript graphing libraries target developers, data scientists,…

Read the review →

Bokeh is an open-source Python library for creating interactive plots, dashboards, and data applications in web browsers. It suits Python developers who want to explore data in notebooks, publish plots on web pages, or build browser…

Read the review →
  1. PlotlyData Visualization Libraries Software 9.3Free plan
  2. BokehData Visualization Libraries Software 8.6Free plan

Strengths and trade-offs

  • Plotly — where it wins

    • 70+ chart and trace types with rich interactive controls
    • Open-source libraries plus cloud and self-hosted deployment
    • Connects with notebooks, databases, Dash, and Streamlit

    Where it doesn't

    • The suite spans several products rather than one packaged application
    • Library-first workflows require Python or JavaScript development
    • Pro pricing is per creator seat, with viewers limited to 10

  • Bokeh — where it wins

    • Offers pan, zoom, hover, tap, and selection tools for interactive plots
    • Supports standalone HTML, embeddable components, and Bokeh server apps
    • Works with Jupyter and a range of Python data sources

    Where it doesn't

    • Its workflow centers on Python rather than general JavaScript charting
    • Server applications require self-hosted deployment
    • Support is through community resources and documentation
  • Plotly9.3/10 · Free plan

    A broad, open-source toolkit for interactive charts, maps, dashboards, and data apps.

    Visit PlotlyFull verdict →
  • Bokeh8.6/10 · Free plan

    A free, open-source Python library for interactive plots, embedded visuals, and server-backed apps.

    Visit BokehFull verdict →

More comparisons

All data visualization libraries software comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update