RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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Edgefinity IoT is a powerful RFID and IoT platform that gives organizations real-time visibility into inventory, assets, equipment, work-in-process, and personnel. By collecting data from RFID readers, sensors, and connected devices, the platform provides a clear view of what is happening across facilities and operations.
Edgefinity IoT helps businesses automate tracking, locate critical assets, monitor movement, verify inventory and shipments, improve production visibility, and support safety applications such as personnel tracking and emergency mustering. Configurable rules and alerts can automatically trigger actions when predefined conditions are met, helping teams respond faster and reduce manual oversight.
Built to work with a wide range of RFID hardware and IoT technologies, Edgefinity IoT can be deployed in the cloud or on-premise and scaled across applications, facilities, and enterprise operations.
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SkySpark
SkyFoundry's software solutions allow clients to get the most out of smart system investments. SkySpark's analytics platform automatically analyzes data from control systems, sensors, and metering systems to identify patterns, deviations, and opportunities for operational improvement and cost reduction. SkySpark assists building owners and operators to "find what matters" from the large amount of data generated by today's smart devices.
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Actcast
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.
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