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AWS Greengrass VS Visual Micro

Compare AWS Greengrass VS Visual Micro and see what are their differences

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AWS Greengrass logo AWS Greengrass

Local compute, messaging, data caching, and synch capabilities for connected devices

Visual Micro logo Visual Micro

Arduino IDE for Visual Studio and Atmel Studio
  • AWS Greengrass Landing page
    Landing page //
    2023-03-28
  • Visual Micro Landing page
    Landing page //
    2023-01-30

AWS Greengrass features and specs

  • Edge Computing
    AWS Greengrass allows devices to process data locally without relying on cloud resources, reducing latency and ensuring continued operation even with intermittent connectivity.
  • Seamless AWS Integration
    Seamlessly integrates with a variety of AWS services such as AWS Lambda, AWS IoT Core, and Amazon S3, allowing for enhanced functionality and simplified data exchange between edge devices and the cloud.
  • Security Features
    Offers robust security features, including data encryption for both in-transit and at-rest data, ensuring secure communication and data storage.
  • OTA Updates
    Provides over-the-air software updates, allowing developers to deploy new updates and patches to edge devices securely and efficiently.
  • Machine Learning at the Edge
    Supports ML inference capabilities, enabling machine learning models to run locally on devices, which is essential for real-time data processing and decision-making.

Possible disadvantages of AWS Greengrass

  • Complexity
    The integration of Greengrass in IoT solutions can add complexity, requiring a good understanding of both AWS services and edge computing.
  • Cost Considerations
    While processing data locally can reduce cloud costs, there may be additional expenses related to maintaining the hardware and ensuring compatibility with Greengrass, as well as costs associated with AWS usage.
  • Device Compatibility
    Not all devices may be compatible with AWS Greengrass, which may limit its use cases or require specific hardware configurations.
  • Dependency on AWS Ecosystem
    Being heavily integrated with the AWS ecosystem means that changes or outages in AWS services can potentially impact Greengrass deployments.
  • Learning Curve
    There may be a steep learning curve for developers who are new to AWS Greengrass, especially when it comes to deploying and managing complex IoT applications.

Visual Micro features and specs

  • Integration with Microsoft Visual Studio
    Visual Micro integrates with Microsoft Visual Studio, allowing users to leverage the powerful features and familiar interface of a professional development environment while working on Arduino projects.
  • Advanced Debugging Features
    It offers advanced debugging capabilities beyond what traditional Arduino IDE provides, such as breakpoints, variable watches, and real-time data tracking, which can greatly enhance the development process.
  • Support for Multiple Boards
    Visual Micro supports a wide range of Arduino boards and compatible devices, making it versatile for various project requirements and allowing developers to work seamlessly across different hardware.
  • Extensive Library Management
    The tool provides comprehensive library management features, making it easier to find, install, and update libraries directly within the development environment.

Possible disadvantages of Visual Micro

  • Complexity for Beginners
    Due to its integration with Visual Studio, the interface may be overwhelming for beginners who are not familiar with complex IDEs, possibly steepening the learning curve.
  • Requires Visual Studio Installation
    Using Visual Micro necessitates having Microsoft Visual Studio installed, which could be a downside for users looking for lightweight or standalone Arduino development solutions.
  • Paid Features
    Some advanced features of Visual Micro are only available in the paid version, which may not be ideal for hobbyists or those looking for completely free tools.
  • Platform Limitations
    As a Windows-based solution requiring Visual Studio, it limits users who work on other operating systems like macOS or Linux from utilizing its features.

AWS Greengrass videos

+ Add

Run ML Models at the Edge with AWS Greengrass ML

Visual Micro videos

+ Add

Visual Micro Tutorials #1: Setup

More videos:

  • Tutorial - Visual Micro Tutorials #5: Advanced Arduino Debugging

Category Popularity

0-100% (relative to AWS Greengrass and Visual Micro)

AWS Greengrass

Visual Micro

Data Dashboard
100 100%
Data Dashboard
0% 0
IDE
0 0%
IDE
100% 100
IoT Platform
100 100%
IoT Platform
0% 0
Electronics
0 0%
Electronics
100% 100

User comments

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Social recommendations and mentions

Based on our record, AWS Greengrass seems to be more popular. It has been mentiond 5 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.

AWS Greengrass mentions (5)

  • Orchestrating Application Workloads in Distributed Embedded Systems: Setting up a Nomad Cluster with AWS IoT Greengrass - Part 1
    In this blog post series, we will demonstrate how to use AWS IoT Greengrass and Hashicorp Nomad to seamlessly interface with multiple interconnected devices and orchestrate service deployments on them. Greengrass will allow us to view the cluster as a single "Thing" from the cloud perspective, while Nomad will serve as the primary cluster orchestration tool. - Source: dev.to / about 2 years ago
  • AWS Summit 2022 Australia and New Zealand - Day 2, AI/ML Edition
    AWS IoT Greengrass allows one to manage their IOT Edge devices, download ML models locally, so that inference can then be also be done locally. - Source: dev.to / about 3 years ago
  • Applying DevOps Principles to Robotics
    To assist in deployment and management of workloads in your fleet, it's worth taking advantage of a fleet or device management tool such as AWS GreenGrass, Formant or Rocos. - Source: dev.to / over 3 years ago
  • Machine Learning Best Practices for Public Sector Organizations
    In some cases, such as with edge devices, inferencing needs to occur even when there is limited or no connectivity to the cloud. Mining fields are an example of this type of use case. AWS IoT Greengrass enables ML inference locally using models that are created, trained, and optimized in the cloud using Amazon SageMaker, AWS Deep Learning AMI, or AWS Deep Learning Containers, and deployed on the edge devices. - Source: dev.to / over 3 years ago
  • Looking for a good IoT overview + a simple tutorial
    Take a look at Greengrass https://aws.amazon.com/greengrass/ Enables OTA updates and fleet management. Source: about 4 years ago

Visual Micro mentions (0)

We have not tracked any mentions of Visual Micro yet. Tracking of Visual Micro recommendations started around Mar 2021.

What are some alternatives?

When comparing AWS Greengrass and Visual Micro, you can also consider the following products

Particle.io - Particle is an IoT platform enabling businesses to build, connect and manage their connected solutions.

Arduino IDE - Arduino is an open-source electronics prototyping platform based on flexible, easy-to-use hardware...

AWS IoT - Easily and securely connect devices to the cloud.

PlatformIO - Next-generation IDE for IoT

Azure IoT Hub - Manage billions of IoT devices with Azure IoT Hub, a cloud platform that lets you easily connect, monitor, provision, and configure IoT devices.

Visuino - Visuino is a visual programming environment that lets you write programs from Arduino circuit boards.

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