Bokeh vs Smoothie Charts

Struggling to choose between Bokeh and Smoothie Charts? 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, Smoothie Charts is a Development product tagged with javascript, charting, streaming, visualization, realtime.

Its standout features include Real-time line, bar, scatter, spline and area charts, Optimized for high performance, Small code footprint, Streaming data visualization, Interactive charts, Time-series charts, Customizable styles, and it shines with pros like Fast and lightweight, Good for real-time data visualization, Easy to integrate, Open source and free.

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:
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


Smoothie Charts

Smoothie Charts

Smoothie Charts is a JavaScript charting library for streaming data visualization. It is optimized for real-time line graphs but also supports bar, scatter, spline and area graphs. Smoothie Charts aims to provide high performance interactive charts with a small footprint.

Categories:
javascript charting streaming visualization realtime

Smoothie Charts Features

  1. Real-time line, bar, scatter, spline and area charts
  2. Optimized for high performance
  3. Small code footprint
  4. Streaming data visualization
  5. Interactive charts
  6. Time-series charts
  7. Customizable styles

Pricing

  • Open Source

Pros

Fast and lightweight

Good for real-time data visualization

Easy to integrate

Open source and free

Cons

Less chart types than some competitors

Limited customization options

Not ideal for static datasets