Struggling to choose between Core Plot and SciDaVis? Both products offer unique advantages, making it a tough decision.
Core Plot is a Development solution with tags like plotting, charting, data-visualization, macos, ios, tvos.
It boasts features such as High performance 2D plotting, Support for bar, line, scatter, pie, area and other plot types, Date plotting with customizable axes, Legend support, Customizable styles and themes, Zooming, panning, and scrolling, Export plots as images, Bind plots to Core Data and load data asynchronously, Mac, iOS, tvOS support and pros including Fast and optimized for mobile, Lightweight and easy to integrate, Good documentation, Active development and support, Very customizable and extensible, Open source and free.
On the other hand, SciDaVis is a Science & Engineering product tagged with data-visualization, plotting, statistics, curve-fitting.
Its standout features include 2D and 3D plotting, Analysis tools like curve fitting and statistics, Import/export data in various formats, Customizable graphs and workspace, Scripting and automation, and it shines with pros like Free and open source, Cross-platform availability, Powerful data visualization, Customizable and extensible via plugins, Supports many file formats.
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.
Core Plot is an open-source 2D plotting framework for macOS, iOS, and tvOS. It provides high-performance plotting, numerical analysis, and data visualization functionality to developers writing native Mac, iPhone, iPad, and Apple TV apps.
SciDaVis is an open-source data analysis and visualization software similar to OriginLab Origin software. It allows interactive plotting of 2D and 3D graphs from imported data, data analysis using curve fitting and statistics tools, and exporting results.