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Description
Actcast is a cutting-edge edge-AI IoT platform service that seamlessly connects real-world events and data to the Internet by executing deep learning inference on edge devices, which facilitates immediate sensing, analysis, and assimilation of physical data with online systems while minimizing both data transfer expenses and privacy concerns. By leveraging edge computing, it allows for the execution of deep learning models directly on affordable hardware like Raspberry Pi, transforming raw inputs from sensors and cameras into meaningful, semantic information that can be relayed to web services or applications. The platform is designed to support the deployment, remote management, and monitoring of IoT applications, referred to as "Acts," across a variety of devices, offering developers essential tools such as an SDK and command-line interface for creating, packaging, and deploying applications within Docker containers that analyze input and deliver condensed outputs. Furthermore, Actcast features capabilities for organizing device groups, setting up triggers and webhooks for event notifications, and managing updates and device statuses through a unified dashboard, ensuring a more streamlined and efficient IoT experience. This comprehensive approach not only enhances operational efficiency but also improves the scalability of IoT solutions.
Description
balenaEngine is a specialized container engine designed specifically for embedded systems and IoT applications, utilizing technology from the Moby Project by Docker. It is significantly smaller than Docker CE, boasting a size reduction of 3.5 times and is distributed as a single binary. This engine is compatible with a diverse range of chipset architectures, catering to everything from small IoT devices to larger industrial gateways. It offers bandwidth-efficient updates using binary diffs that can be 10 to 70 times smaller compared to the traditional method of pulling layers in various scenarios. To mitigate excessive disk writing and safeguard against potential storage corruption, it extracts layers as they are received. Additionally, its atomic and durable image pulls ensure protection against incomplete container downloads in case of power interruptions. The design also minimizes page cache thrashing during image pulls, allowing applications to run smoothly even in low-memory environments. In summary, balenaEngine is an innovative solution that not only supports Docker containers but also enhances bandwidth efficiency for container updates. This makes it an ideal choice for developers seeking reliability and efficiency in IoT and embedded systems.
API Access
Has API
API Access
Has API
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
Actcast
Founded
2018
Country
United States
Website
actcast.io
Vendor Details
Company Name
balena
Founded
2013
Country
United States
Website
www.balena.io/engine/
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
Product Features
Container Management
Access Control
Application Development
Automatic Scaling
Build Automation
Container Health Management
Container Storage
Deployment Automation
File Isolation
Hybrid Deployments
Network Isolation
Orchestration
Shared File Systems
Version Control
Virtualization
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization