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  5. AWS Greengrass vs AWS IoT Device Management

AWS Greengrass vs AWS IoT Device Management

OverviewComparisonAlternatives

Overview

AWS Greengrass
AWS Greengrass
Stacks25
Followers79
Votes0
AWS IoT Device Management
AWS IoT Device Management
Stacks48
Followers71
Votes0

AWS Greengrass vs AWS IoT Device Management: What are the differences?

  1. Deployment Model: AWS Greengrass allows you to run AWS Lambda functions and keep device data in sync with AWS IoT Core while offline. On the other hand, AWS IoT Device Management is focused on managing the lifecycle of IoT devices such as onboarding, organizing, monitoring, and remotely updating devices.

  2. Functionality: AWS Greengrass provides local compute, messaging, data caching, and synchronization services for connected devices. In contrast, AWS IoT Device Management focuses on managing fleets of devices at scale, offering features such as device registration, monitoring, and remote management.

  3. Integration with Other Services: AWS Greengrass integrates seamlessly with other AWS services like Amazon S3, AWS Lambda, and Amazon Kinesis. AWS IoT Device Management, on the other hand, is tightly integrated with AWS IoT Core and provides device management capabilities specific to IoT devices.

  4. Offline Capabilities: AWS Greengrass enables devices to operate locally with reduced latency and provides a seamless experience when connection to the cloud is intermittent. AWS IoT Device Management primarily relies on a cloud-based approach for device management tasks.

  5. Edge Computing Focus: AWS Greengrass is designed for edge computing scenarios where data processing and analysis are performed closer to the data source. AWS IoT Device Management, on the other hand, focuses on centralized device management from the cloud.

  6. Target Use Cases: AWS Greengrass is suitable for scenarios where low latency, offline operation, and local computation are essential, such as industrial automation and smart homes. AWS IoT Device Management is more relevant for managing large fleets of IoT devices efficiently, ensuring their security and compliance.

In Summary, AWS Greengrass focuses on enabling edge computing capabilities for IoT devices with offline operation, while AWS IoT Device Management is tailored for managing fleets of IoT devices efficiently from the cloud.

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Detailed Comparison

AWS Greengrass
AWS Greengrass
AWS IoT Device Management
AWS IoT Device Management

Greengrass lets you run IoT applications seamlessly across the AWS cloud and local devices using AWS Lambda and AWS IoT.

AWS IoT Device Management makes it easy to securely onboard, organize, monitor, and remotely manage IoT devices at scale. IoT Device Management lets you register your devices individually or in bulk, and manage permissions so that devices remain secure. Then, you use the IoT Device Management console to organize your devices into groups, monitor and troubleshoot device functionality, and send remote updates to your devices.

Respond to local events in near real-time;Operate offline
Easily onboard connected devices in bulk; Organize connected devices into groups; Fleet indexing and search; Fine-grained device logging; Remotely manage connected devices
Statistics
Stacks
25
Stacks
48
Followers
79
Followers
71
Votes
0
Votes
0
Integrations
No integrations available
Amazon IoT
Amazon IoT

What are some alternatives to AWS Greengrass, AWS IoT Device Management?

Amazon IoT

Amazon IoT

AWS IoT is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices. AWS IoT can support billions of devices and trillions of messages, and can process and route those messages to AWS endpoints and to other devices reliably and securely. With AWS IoT, your applications can keep track of and communicate with all your devices, all the time, even when they aren’t connected.

Node-RED

Node-RED

It is a programming tool for wiring together hardware devices, APIs and online services in new and interesting ways.

Azure IoT Hub

Azure IoT Hub

Use device-to-cloud telemetry data to understand the state of your devices and define message routes to other Azure services without writing any code. In cloud-to-device messages, reliably send commands and notifications to your connected devices and track message delivery with acknowledgement receipts. Device messages are sent in a durable way to accommodate intermittently connected devices.

Google Cloud IoT Core

Google Cloud IoT Core

Cloud IoT Core is a fully managed service that allows you to easily and securely connect, manage, and ingest data from millions of globally dispersed devices. Cloud IoT Core, in combination with other services on Google Cloud IoT platform, provides a complete solution for collecting, processing, analyzing, and visualizing IoT data in real time to support improved operational efficiency.

Resin.io

Resin.io

Balena makes it simple to deploy, update, and maintain code running on remote devices.

Bespoken Tools

Bespoken Tools

Bespoken makes it easy to develop for Alexa, Google Home and Chatbots. We provide logging, analytics, and our rapid development CLI.

Losant

Losant

Losant is a complete developer platform for quickly, easily, and securely building connected experiences and solutions.

ThingWorx

ThingWorx

It is a complete, end-to-end technology platform designed for the industrial Internet of Things (IIoT). It delivers tools and technologies that empower businesses to rapidly develop and deploy powerful applications and augmented reality (AR) experiences.

Autodesk SeeControl

Autodesk SeeControl

Autodesk SeeControl is an enterprise IoT cloud service that helps manufacturers to connect, analyze, and manage their products. It virtualizes machines, links them with reporting devices, and through analytics unlocks the data trapped inside—utilizing the unlimited computing power of a cloud native architecture.

AWS IoT SiteWise

AWS IoT SiteWise

It is a managed service that makes it easy to collect, store, organize, and monitor data from industrial equipment at scale to help you make better, data-driven decisions. You can use it to monitor operations across facilities, quickly compute common industrial performance metrics, and create applications that analyze industrial equipment data to prevent costly equipment issues and reduce gaps in production. This allows you to collect data consistently across devices, identify issues with remote monitoring more quickly, and improve multi-site processes with centralized data.

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