Bokeh vs Plotly

Struggling to choose between Bokeh and Plotly? Both products offer unique advantages, making it a tough decision.

Bokeh is a Development solution with tags like python, data-visualization, interactive, graphics, web-browser.

It boasts features such as Interactive data visualization, Supports streaming data, Python library, Targets modern web browsers, Elegant and concise graphics, High-performance interactivity, Can handle large datasets and pros including Very flexible and customizable visualizations, Integrates well with other Python data tools like NumPy and Pandas, Open source and free, Good performance even with large datasets, Nice web-based interface for sharing visualizations.

On the other hand, Plotly is a Data Visualization product tagged with python, r, javascript, excel, data-analysis, data-visualization, interactive, charts, graphs, dashboards.

Its standout features include Interactive data visualization, Support for Python, R, JavaScript, Excel, 2D and 3D plotting, Statistical charts, Dashboards, Collaboration tools, Exporting and sharing, and it shines with pros like User-friendly, High-quality visualizations, Cross-platform compatibility, Open source and free, Large gallery of examples, Active community support.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Bokeh

Bokeh

Bokeh is an interactive data visualization library for Python that targets modern web browsers for presentation. It offers elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.

Categories:
Development Data Visualization
python data-visualization interactive graphics web-browser

Bokeh Features

  1. Interactive data visualization
  2. Supports streaming data
  3. Python library
  4. Targets modern web browsers
  5. Elegant and concise graphics
  6. High-performance interactivity
  7. Can handle large datasets

Pricing

  • Open Source

Pros

Very flexible and customizable visualizations

Integrates well with other Python data tools like NumPy and Pandas

Open source and free

Good performance even with large datasets

Nice web-based interface for sharing visualizations

Cons

Steeper learning curve than some visualization libraries

Visualizations can be more complex to build

Limited built-in statistical analysis features

Requires knowledge of Python and web development

Not as simple as drag-and-drop visualization builders

Plotly

Plotly

Plotly is an open-source graphing library for Python, R, JavaScript, and Excel. It allows users to create interactive, publication-quality graphs, charts, and dashboards that can be embedded in websites and apps. Plotly is useful for data analysis and visualization.

Categories:
Data Visualization Interactive Charting
python r javascript excel data-analysis data-visualization interactive charts graphs dashboards

Plotly Features

  1. Interactive data visualization
  2. Support for Python, R, JavaScript, Excel
  3. 2D and 3D plotting
  4. Statistical charts
  5. Dashboards
  6. Collaboration tools
  7. Exporting and sharing

Pricing

  • Freemium
  • Subscription-based

Pros

User-friendly

High-quality visualizations

Cross-platform compatibility

Open source and free

Large gallery of examples

Active community support

Cons

Steep learning curve

Limited customization compared to matplotlib

Online dependency for full functionality

Freemium pricing model limits features