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Average Ratings 0 Ratings
Description
AWS IoT Greengrass effectively brings the capabilities of AWS to edge devices, enabling them to locally process the data they create while still leveraging the cloud for management, analysis, and reliable storage solutions. This platform allows connected devices to execute AWS Lambda functions, run Docker containers, or utilize both, enabling real-time predictions based on machine learning models, maintaining data synchronization, and ensuring secure communication among devices—even in the absence of an internet connection. With AWS IoT Greengrass, developers can utilize familiar programming languages and models to design and validate their device applications in the cloud before deploying them to the actual devices. Furthermore, this service can be configured to filter and manage device data, ensuring only essential information is sent back to AWS. Additionally, AWS IoT Greengrass offers seamless integration with third-party applications, local software solutions, and a range of AWS services through its Connectors, enhancing the overall functionality and versatility of edge computing. By incorporating these features, AWS IoT Greengrass empowers businesses to maximize the potential of their connected devices while maintaining operational efficiency.
Description
The Internet of Things (IoT) encompasses billions of physical devices globally that are interconnected and actively gathering and sharing data. By leveraging IoT data alongside IBM Cloud® technologies, organizations can derive meaningful insights that enhance nearly every facet of their operations while also paving the way for innovative business models. Begin by linking your device to an IBM Cloud recipe, utilizing open and lightweight protocols like MQTT or HTTP for connectivity. Efficient management of connected devices allows applications to access both real-time and historical data. Secure APIs facilitate the integration of your applications with the data generated by these devices, enabling seamless interaction. You can develop analytical applications either within the IBM Cloud, on another cloud platform, or on your own servers. The IBM Watson IoT® Platform provides a straightforward method to connect, gather, and process IoT data quickly. Additionally, you can leverage the analytics service for effective visualization and AI-enhanced analytics in the cloud, leading to informed decision-making and operational efficiency. This integration ultimately transforms the way businesses operate and create value in the digital landscape.
API Access
Has API
API Access
Has API
Integrations
AWS Connected Vehicle Solution
AWS IoT Device Defender
IBM Cloud
IBM Cloud Messages for RabbitMQ
IBM Watson IoT Platform
Vilicom GIGAWAVE
Integrations
AWS Connected Vehicle Solution
AWS IoT Device Defender
IBM Cloud
IBM Cloud Messages for RabbitMQ
IBM Watson IoT Platform
Vilicom GIGAWAVE
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/greengrass/
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/cloud/internet-of-things
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
Product Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization