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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Airlock Digital
Airlock Digital delivers an easy-to-manage and scalable application control solution to protect endpoints with confidence. Built by cybersecurity professionals and trusted by organizations worldwide, Airlock Digital enforces a Deny by Default security posture to block all untrusted code, including unknown applications, unwanted scripts, malware, and ransomware.
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Ansys BladeModeler
Ansys BladeModeler is a user-friendly software specifically designed for the swift creation of 3D models of rotating machinery parts. This tool facilitates the design of various types of blade components, including axial, mixed-flow, and radial blades, which are essential in devices such as pumps, compressors, fans, blowers, turbines, expanders, turbochargers, and inducers, among others. Ansys BladeModeler seamlessly integrates with Ansys DesignModeler, providing robust 3D geometry modeling capabilities that enable the addition of numerous geometric features, including hub metal, blade fillets, and various cut-offs and trims. The software allows for the combination of blade designs with non-bladed components, such as housings, blade roots, or intricate 3D tip regions, enhancing design flexibility. These non-bladed elements can be either created within the software or imported through CAD connections compatible with all leading CAD platforms, ensuring limitless design possibilities for assembly and evaluation. Users also have the option to select the degree of geometric detail they wish to incorporate into their analyses, tailoring the experience to their specific engineering needs. This versatility makes Ansys BladeModeler an invaluable tool for engineers looking to innovate in the field of rotating machinery design.
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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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