
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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Macaw AMS can be used to sell Insurance. Macaw AMS can be used by brokers, MGAs or MGUs, Program Managers, and Lloyds Coverholders to automate their operations.
Macaw AMS was built with a customer-centric approach. It supports CRM, Sales and Underwriting. Customers, producers, and service providers can access self-service portals.
Macaw AMS has built-in Document Management and Task Management capabilities. It is equipped with adaptors that allow for integrated and in-flow services such as eSignature, Payments, OFAC checks, Mass Emailing, Computer Telephony, and Mass Emailing, using 3rd Party Services.
The data analytics part of Macaw AMS offers powerful data visualization with predefined dashboards, allowing users to easily upload datasets and view dynamic charts for clear, multi-dimensional insights. Interactive, real-time visualizations help uncover trends and insights, driving informed decision-making.
Macaw AMS is hosted on cloud and tested for cybersecurity. The database is relational, and the core components of the Java-based application are written in Java. Macaw AMS is capable of processing 500-1000 policies per day at its peak.
Macaw AMS is expected reduce per policy costs by 30%.
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Open Automation Software
Open Automation Software IIoT platform Windows and Linux allows you to liberate your Industry4.0 data. OAS is an unlimited IoT Gateway that works with Windows, Linux, Raspberry Pi 4 and Windows IoT Core. It can also be used to deploy Docker containers.
HMI visualizations for web, WPF, WinForm C#, and VB.NET applications.
Log data and alarms to SQL Server and MS Access, SQL Server, Oracle and MS Access, MySQL and Azure SQL, PostgreSQL and Cassandra.
MQTT Broker and Client interface, as well as cloud connectivity to Azure IoT Gateway and AWS IoT Gateway.
Remote Excel Workbooks can be used to read and write data.
Notifications of alarm sent to voice, SMS text and email.
Access to programmatic information via REST API and.NET
Allen Bradley ControlLogix and CompactLogix, GuardLogix. Micro800, MicroLogix. MicroLogix. SLC 500. PLC-5.
Siemens S7-220, S7-3300, S7-405, S7-490, S7-1200, S7-1500, and S7-1500
Modbus TCP and Modbus RTU are Modbus ASCII and Modbus TCP for Master and Slave communication.
OPTO-22, MTConnect and OPC UA, OPC DA.
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Apache Kafka
Apache Kafka® is a robust, open-source platform designed for distributed streaming. It can scale production environments to accommodate up to a thousand brokers, handling trillions of messages daily and managing petabytes of data with hundreds of thousands of partitions. The system allows for elastic growth and reduction of both storage and processing capabilities. Furthermore, it enables efficient cluster expansion across availability zones or facilitates the interconnection of distinct clusters across various geographic locations. Users can process event streams through features such as joins, aggregations, filters, transformations, and more, all while utilizing event-time and exactly-once processing guarantees. Kafka's built-in Connect interface seamlessly integrates with a wide range of event sources and sinks, including Postgres, JMS, Elasticsearch, AWS S3, among others. Additionally, developers can read, write, and manipulate event streams using a diverse selection of programming languages, enhancing the platform's versatility and accessibility. This extensive support for various integrations and programming environments makes Kafka a powerful tool for modern data architectures.
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