Software Alternatives, Accelerators & Startups

OpenCV VS Bryntum

Compare OpenCV VS Bryntum and see what are their differences

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OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library

Bryntum logo Bryntum

High performance web components for SaaS apps - including Gantt, Scheduler, Grid, Calendar and Kanban widgets. Seamless integration with React, Vue, Angular or plain JS apps.
  • OpenCV Landing page
    Landing page //
    2023-07-29
  • Bryntum
    Image date //
    2024-12-28
  • Bryntum
    Image date //
    2024-12-28
  • Bryntum
    Image date //
    2024-12-28
  • Bryntum
    Image date //
    2024-12-28

Tired of building scheduling features from scratch? Bryntumโ€™s high-performance components handle the heavy lifting - no more date-time nightmares. Our JavaScript widgets (Scheduler, Data Grid, Gantt, TaskBoard, Calendar) integrate seamlessly with React, Angular, or Vue. They process massive datasets, deliver fast rendering, and adapt to your style. With robust docs, flexible APIs, and dedicated support, Bryntum helps you build top-tier apps without the late-night debugging.

Bryntum

$ Details
Free Trial $850.0 / One-off (OEM license for commercial use)
Platforms
React Angular Vue JavaScript TypeScript
Release Date
2009 September
Startup details
Country
Sweden
City
Stockholm
Founder(s)
Mats Bryntse
Employees
10 - 19

OpenCV features and specs

  • Comprehensive Library
    OpenCV offers a wide range of tools for various aspects of computer vision, including image processing, machine learning, and video analysis.
  • Cross-Platform Compatibility
    OpenCV is designed to run on multiple platforms, including Windows, Linux, macOS, Android, and iOS, which makes it versatile for development across different environments.
  • Open Source
    Being open-source, OpenCV is freely available for use and allows developers to inspect, modify, and enhance the code according to their needs.
  • Large Community Support
    A large community of developers and researchers actively contributes to OpenCV, providing extensive support, tutorials, forums, and continuously updated documentation.
  • Real-Time Performance
    OpenCV is highly optimized for real-time applications, making it suitable for performance-critical tasks in various industries such as robotics and interactive installations.
  • Extensive Integration
    OpenCV can easily be integrated with other libraries and frameworks such as TensorFlow, PyTorch, and OpenCL, enhancing its capabilities in deep learning and GPU acceleration.
  • Rich Collection of examples
    OpenCV provides a large number of example codes and sample applications, which can significantly reduce the learning curve for beginners.

Possible disadvantages of OpenCV

  • Steep Learning Curve
    Due to the vast array of functionalities and the complexity of some of its advanced features, beginners may find it challenging to learn and use effectively.
  • Documentation Gaps
    While the documentation is extensive, it can sometimes be incomplete or outdated, requiring users to rely on community forums or external sources for solutions.
  • Resource Intensive
    Some functions and algorithms in OpenCV can be quite resource-intensive, requiring significant processing power and memory, which can be a limitation for low-end devices.
  • Limited High-Level Abstractions
    OpenCV provides a wealth of low-level functions, but it may lack higher-level abstractions and frameworks, necessitating more hands-on coding and algorithm development.
  • Dependency Management
    Setting up and managing dependencies can be cumbersome, especially when integrating OpenCV with other libraries or on certain operating systems.
  • Backward Compatibility Issues
    With frequent updates and new versions, backward compatibility can sometimes be problematic, potentially breaking existing code when updating.

Bryntum features and specs

  • Drag-drop
    Drag drop and resize any task
  • RTL
    Right-to-Left support
  • Import & Export
    Export + Import from MS Project / Excel
  • WCAG 2.1
    Fully accessible
  • Travel time
    Visualize travel time for each task
  • Easy theming
    Roll your own theme or customize one of the built-in ones
  • Dark theme
    For working late
  • High performance
    Handles tens of thousands of tasks/rows
  • UX
    Excellent UX your users will love
  • AI Copilot
    In-product AI assistant letting you navigate and schedule using natural language

Analysis of OpenCV

Overall verdict

  • Yes, OpenCV is considered a good and reliable choice for computer vision tasks, particularly due to its extensive functionality, active community, and flexibility.

Why this product is good

  • OpenCV (Open Source Computer Vision Library) is widely regarded as a robust and versatile library for computer vision applications. It offers a comprehensive collection of functions and algorithms for image processing, video capture, machine learning, and more. Its open-source nature encourages community involvement, making it highly adaptable and continuously improving. OpenCV's cross-platform support and ease of integration with other libraries and languages further enhance its appeal.

Recommended for

  • Developers and researchers working on computer vision projects
  • People looking to implement real-time video analysis
  • Individuals exploring machine learning applications related to image and video processing
  • Anyone interested in experimenting with or learning computer vision concepts

OpenCV videos

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Bryntum videos

Boost your app UX with Bryntum

More videos:

  • Demo - Flight dispatch scheduling demo with Bryntum Scheduler Pro

Category Popularity

0-100% (relative to OpenCV and Bryntum)
Data Science And Machine Learning
Project Management
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Javascript UI Libraries
0 0%
100% 100

Questions and Answers

As answered by people managing OpenCV and Bryntum.

How would you describe your primary audience?

Bryntum's answer:

Bryntum primarily targets professional software teams - particularly frontend developers, architects, UX, and technical leads who need robust scheduling and project-planning functionality for their web applications. Our products (such as the Scheduler and Gantt components) are designed for organizations that want to integrate sophisticated resource management, timeline visualization, and interactive scheduling into existing or new software solutions.

In practice, these teams often work in industries and use cases where precise scheduling is critical (e.g., project management, construction, healthcare, manufacturing, and IT services). While developers are the day-to-day implementers of Bryntumโ€™s products, managers or product owners (such as PMO leads or development managers) also play a role in evaluating Bryntumโ€™s solutions to ensure they meet the organizationโ€™s technical and business requirements.

What makes your product unique?

Bryntum's answer:

What Makes Bryntum Unique?

Bryntum stands out because of its laser focus on high-performance, enterprise-grade JavaScript componentsโ€”particularly around scheduling and project planning. Here are a few reasons why Bryntum is unique:

  1. Advanced Scheduling Expertise
    Bryntumโ€™s Scheduler and Gantt products are widely recognized for their sophisticated scheduling capabilities. Their tools handle complex resource allocations, dependencies, drag-and-drop reordering, and timeline visualizationsโ€”making them a go-to choice for project and resource management in large-scale applications.

  2. Pure JavaScript (Framework Agnostic)
    All Bryntum components are developed using modern, pure JavaScript. This means they can easily integrate into any tech stack or framework (React, Angular, Vue, etc.) without sacrificing functionality or performance. If you switch frameworks in the future, you can keep using Bryntumโ€™s components with minimal refactoring.

  3. Performance & Scalability
    Bryntum components are designed for high-volume data rendering. Whether itโ€™s thousands of tasks in a Gantt chart or a scheduler loaded with numerous resources, Bryntumโ€™s products can handle heavy data loads smoothly and maintain snappy interactions.

  4. Robust Feature Set
    From critical-path analysis in Gantt charts to resource histograms and timeline overviews, Bryntum packs advanced features that meet enterprise project-planning requirements. This feature depth is one reason many organizations choose Bryntum over more general-purpose grid libraries.

  5. Extensive Documentation & Demos
    Bryntum provides thorough documentation, live examples, and demo apps that showcase how to integrate its components into a variety of environments. This makes it easier for developers to learn the product and quickly build prototypes.

  6. Dedicated Support & Development
    A hallmark of Bryntum is its attentive support. Their engineering and support teams are responsive and highly knowledgeable about both front-end development and project-planning logic, which speeds up troubleshooting and feature requests.

By focusing on scheduling and project-planning tools with high performance, great flexibility, and deep functionality, Bryntum has carved out a niche that sets it apart from other libraries and component vendors.

Why should a person choose your product over its competitors?

Bryntum's answer:

Performance, UX and abundance of features.

Which are the primary technologies used for building your product?

Bryntum's answer:

JavaScript, TypeScript and CSS

What's the story behind your product?

Bryntum's answer:

Bryntum was founded by Mats Bryntse, a software developer from Stockholm, Sweden, who had a deep interest in creating advanced scheduling solutions for web applications. Originally, Bryntum began as a consulting and component-development company centered around Sencha Ext JS, one of the leading JavaScript frameworks in the late 2000s.

Early Days (Ext Scheduler & Gantt)

Mats Bryntse developed the first version of Ext Scheduler, a scheduling component based on Ext JS, in response to a growing demand for an interactive resource-scheduling tool in web applications. Building on the success of Ext Scheduler, Bryntum introduced a Gantt component, allowing developers to visualize and manage project tasks, dependencies, and timelines directly in the browser. Transition to Pure JavaScript

Over time, the JavaScript ecosystem expanded to include many popular frameworks (React, Angular, Vue, etc.). Instead of maintaining separate builds for each, Bryntum decided to make its components framework agnostic, rebuilding them as pure JavaScript libraries. This shift allowed Bryntumโ€™s tools to be integrated into virtually any front-end stack while delivering the same level of performance and scheduling sophistication.

Who are some of the biggest customers of your product?

Bryntum's answer:

  • Apple
  • Netflix
  • SpaceX
  • Intel
  • Disney
  • US Navy
  • Airbus
  • American Airlines
  • AstraZeneca
  • Coca-Cola

Over 5,000 customers in 80 countries: https://bryntum.com/company/customers/

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare OpenCV and Bryntum

OpenCV Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
10 Python Libraries for Computer Vision
OpenCV is the go-to library for computer vision tasks. It boasts a vast collection of algorithms and functions that facilitate tasks such as image and video processing, feature extraction, object detection, and more. Its simple interface, extensive documentation, and compatibility with various platforms make it a preferred choice for both beginners and experts in the field.
Source: clouddevs.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
OpenCV is an open-source computer vision and machine learning software library that was first released in 2000. It was initially developed by Intel, and now it is maintained by the OpenCV Foundation. OpenCV provides a set of tools and software development kits (SDKs) that help developers create computer vision applications. It is written in C++, but it supports several...
Source: www.uubyte.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
These are some of the most basic operations that can be performed with the OpenCV on an image. Apart from this, OpenCV can perform operations such as Image Segmentation, Face Detection, Object Detection, 3-D reconstruction, feature extraction as well.
Source: neptune.ai
5 Ultimate Python Libraries for Image Processing
Pillow is an image processing library for Python derived from the PIL or the Python Imaging Library. Although it is not as powerful and fast as openCV it can be used for simple image manipulation works like cropping, resizing, rotating and greyscaling the image. Another benefit is that it can be used without NumPy and Matplotlib.

Bryntum Reviews

We have no reviews of Bryntum yet.
Be the first one to post

Social recommendations and mentions

Based on our record, OpenCV seems to be more popular. It has been mentiond 61 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

OpenCV mentions (61)

  • What is the Most Effective AI Tool for App Development Today?
    Google's Gemini and other multimodal models also fit here, especially for mixed-input apps. James Allsopp, Founder of Ask Zyro, suggests, "For anything involving images or mixed inputs, tools like Claude 3 Opus (great for handling long context) or Google's Gemini can work well, depending on what you need for your user interface." These frameworks excel in scenarios requiring visual understanding, such as augmented... - Source: dev.to / about 2 months ago
  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isnโ€™t just a tool, itโ€™s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that donโ€™t just interpret visuals, but... - Source: dev.to / 5 months ago
  • Top Programming Languages for AI Development in 2025
    Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / 5 months ago
  • Why 2024 Was the Best Year for Visual AI (So Far)
    Almost everyone has heard of libraries like OpenCV, Pytorch, and Torchvision. But there have been incredible leaps and bounds in other libraries to help support new tasks that have helped push research even further. It would be impossible to thank each and every project and the thousands of contributors who have helped make the entire community better. MedSAM2 has been helping bring the awesomeness of SAM2 to the... - Source: dev.to / 9 months ago
  • 20 Open Source Tools I Recommend to Build, Share, and Run AI Projects
    OpenCV is an open-source computer vision and machine learning software library that allows users to perform various ML tasks, from processing images and videos to identifying objects, faces, or handwriting. Besides object detection, this platform can also be used for complex computer vision tasks like Geometry-based monocular or stereo computer vision. - Source: dev.to / 11 months ago
View more

Bryntum mentions (0)

We have not tracked any mentions of Bryntum yet. Tracking of Bryntum recommendations started around Dec 2024.

What are some alternatives?

When comparing OpenCV and Bryntum, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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NumPy - NumPy is the fundamental package for scientific computing with Python

DHTMLX - JavaScript Library for cross-platform web and mobile app development with HTML5 JavaScript widgets. Easy integration with popular JavaScript Frameworks.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Schedule-X.dev - Modern JavaScript Event calendar for React, Angular, Vue and plain JS. Modern alternative to Fullcalendar. Drag & drop, dark mode, event resizing and more.