jqPlot VS Core Plot

• Customizability
  jqPlot offers extensive customization options, allowing users to tailor charts extensively to fit specific aesthetic and functional requirements.
• Chart Variety
  It supports a wide range of chart types including line, bar, pie, and many more, providing flexibility in data representation.
• Open Source
  As an open-source library, it is free to use and can be modified to suit specific project needs.
• Plugin Support
  jqPlot has a plugin architecture that enables users to extend functionality easily by adding new rendering options or features.

Possible disadvantages

• Performance Issues
  jqPlot may not perform as well compared to other libraries when dealing with large datasets or complex charts.
• Limited Interactivity
  The library provides basic interactivity, but lacks advanced interactive features seen in other data visualization tools.
• Slower Development
  Development and updates for jqPlot are slower, potentially lagging behind in introducing new features or keeping up with modern web standards.
• Dependency on jQuery
  jqPlot is heavily dependent on jQuery, which can be a limitation as many projects are moving towards using vanilla JavaScript or other frameworks.

• Open Source
  Core Plot is open source, which means it is free to use and allows developers to contribute to its improvement and customization.
• Customizability
  Core Plot offers extensive customization options, giving developers control over the appearance and behavior of their plots.
• Cross-Platform Support
  Core Plot can be used for both iOS and macOS applications, making it a versatile option for developers working across Apple platforms.
• Feature-Rich
  It provides a wide range of features like axis labels, data plots, and complex graphing capabilities suitable for creating detailed and informative charts.
• Active Community
  The Core Plot library has an active community of developers that contribute to the repository and provide support through forums and documentation.

Possible disadvantages

• Complexity
  The library can be complex to use, especially for developers who are new to Core Plot or data visualization, due to its extensive feature set.
• Limited Documentation
  While the community is active, the official documentation may not be as comprehensive as needed, which might hinder the learning curve.
• Performance
  For very large datasets, Core Plot may experience performance issues, as it's not specifically optimized for handling huge volumes of data.
• Learning Curve
  Due to its complexity and feature-rich nature, users may find there is a significant learning curve to effectively utilizing Core Plot.
• Maintenance
  Like many open-source projects, the level of maintenance and speed of updates rely heavily on community contributions, which may result in slower updates or bug fixes.

Tracking jqPlot since Mar 2021.

• How Fast is SciChart’s iOS Chart?

  To carry out performance tests we've built a iOS Chart comparison application in Objective-C. This application performs a number of identical tests on the four chart providers: Core Plot, iOS Charts, Shinobi and SciChart and outputs the... - Source: dev.to / over 2 years ago