Everyware Cloud Description
Everyware Cloud (EC) is an Internet of Things (IoT) integration platform developed and maintained by Eurotech. Built on the foundation of Eclipse Kapua, Everyware Cloud features a flexible and open IoT cloud platform that utilizes a microservices architecture. It facilitates comprehensive device management, diagnostics, provisioning, remote access to IoT gateways and devices, as well as integration services for telemetry data. By enabling remote access, users can conduct maintenance and troubleshoot issues without the need for physical visits to the installation site. You can rely on your remote devices thanks to the robust enterprise-level security measures embedded within the Everyware Cloud IoT Platform. Additionally, the platform helps lower integration costs through the use of standard-based interfaces. Device connectivity is supported by the ISO-certified MQTT protocol and employs an open, language-independent data payload format. This ensures seamless communication and data exchange across diverse devices and applications. Overall, Everyware Cloud stands out as a comprehensive solution for managing IoT ecosystems efficiently and securely.
Everyware Cloud Alternatives
TRACTIAN
Tractian is the Industrial Copilot for maintenance and reliability, combining hardware and software solutions to monitor asset performance, manage industrial operations, and implement predictive maintenance strategies. Its AI-driven platform empowers businesses to prevent unplanned equipment downtime and boost production output. The company is headquartered in Atlanta, GA, and extends its presence globally with offices in Mexico City and Sao Paulo. Learn more at tractian.com.
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HiveMQ
The HiveMQ Platform provides a scalable, reliable data backbone with an event-driven MQTT architecture. Here are a few highlights:
1. MQTT Broker: At the heart of the HiveMQ platform is a fully MQTT-compliant broker purpose-built for fast, reliable, bi-directional data movement between IoT devices and enterprise systems.
2. Edge Data Integration: HiveMQ Edge seamlessly integrates edge data by converting industrial protocols into standardized MQTT, enabling an interoperable IIoT infrastructure.
3. IoT Streaming Governance: Data Hub transforms data in flight, passing only the most relevant, contextualized data to cloud and enterprise systems.
4. UNS & IT/OT convergence Enabler: Commonly used as the backbone for Unified Namespace architectures and seamlessly connects OT devices with IT systems for full visibility and interoperability.
5. Distributed Data Intelligence: HiveMQ Pulse unifies and contextualizes data across the enterprise for smarter decisions exactly where they matter most.
6. Maximum Interoperability: Runs anywhere on-premises or in public or private clouds. Efficiently connects to streaming applications, databases and data lakes with a Java SDK to build your own
7. Scalability to Support Growth: Elastic scaling with automatic data balancing and smart message distribution. Proven benchmark of up to 200M active clients with 1.8B messages/hour
8. Business Critical Reliability: Zero message loss with persistence to disk and offline queuing. No single point of failure due to masterless cluster architecture and zero downtime upgrades
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AWS IoT
There are countless devices operating in various environments such as residences, industrial sites, oil extraction facilities, medical centers, vehicles, and numerous other locations. As the number of these devices continues to rise, there is a growing demand for effective solutions that can connect them, as well as gather, store, and analyze the data they generate. AWS provides a comprehensive suite of IoT services that span from edge computing to cloud-based solutions. Unique among cloud providers, AWS IoT integrates data management with advanced analytics capabilities tailored to handle the complexities of IoT data seamlessly. The platform includes robust security features at every level, offering preventive measures like encryption and access control to safeguard device data, along with ongoing monitoring and auditing of configurations. By merging AI with IoT, AWS enhances the intelligence of devices, allowing users to build models in the cloud and deploy them to devices where they operate twice as efficiently as comparable solutions. Additionally, you can streamline operations by easily creating digital twins that mirror real-world systems and conduct analytics on large volumes of IoT data without the need to construct a dedicated analytics infrastructure. This means businesses can focus more on leveraging insights rather than getting bogged down in technical complexities.
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ESF Edge Computing Platform
Edge Computing allows for data processing to occur closer to its source, effectively at the network's edge. By doing so, it minimizes the communication bandwidth required between sensors and centralized data centers, as analytics and insights are generated locally. The IoT service gateway model, which utilizes robust enterprise software stacks and operates as a controller and aggregator at the edge of IoT systems, serves as an ideal basis for implementing Edge Computing solutions. Eurotech’s Everyware Software Framework (ESF) stands out as a commercial, enterprise-ready variant of Eclipse Kura, an open-source platform designed for Edge Computing in IoT gateways. Supported and distributed by Eurotech, ESF enriches Eclipse Kura with sophisticated features that enhance security, diagnostics, provisioning, remote access, and seamless integration with Everyware Cloud, Eurotech's IoT Integration Platform. Consequently, this approach not only strengthens the capabilities of IoT deployments but also fosters greater efficiency in data handling.
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Integrations
Company Details
Company:
Eurotech
Year Founded:
1992
Headquarters:
Italy
Website:
www.eurotech.com
Media
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
Customer Support
Business Hours
Online Support
Everyware Cloud Features and Options
IoT Software
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
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