RaimaDB
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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Shoplogix Smart Factory Platform
For over two decades, Shoplogix has helped leading manufacturers worldwide unlock hidden production potential by transforming real-time machine and performance data into actionable insights. The platform automatically captures signals like downtime, scrap, and throughput, delivering visual dashboards that enable teams to identify bottlenecks, reduce losses, and improve continuously—both during shifts and in post-shift analysis.
With OneSignal connectivity, Shoplogix integrates with any machine brand or type to deliver real-time, granular insights on slow-running, starved, or idle machines. Its intuitive visual management system allows operators and managers alike to quickly detect and act on issues. Integrated analytics provide powerful, slice-and-dice capabilities similar to leading BI tools, without leaving the platform.
Designed for agility, Shoplogix supports scaling from a single line to multi-plant operations across geographies. Continuous improvement tools like Action Plans and Digital Andon alerts keep teams engaged, aligned, and empowered to act—making Shoplogix a powerful ally in the pursuit of operational excellence.
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FreeRTOS
Developed in collaboration with top chip manufacturers over a span of 15 years, FreeRTOS is now downloaded approximately every 170 seconds and stands as a top-tier real-time operating system (RTOS) tailored for microcontrollers and small microprocessors. Available at no cost under the MIT open source license, FreeRTOS encompasses a kernel along with an expanding collection of IoT libraries that cater to various industries. Prioritizing reliability and user-friendliness, FreeRTOS is renowned for its proven durability, minimal footprint, and extensive device compatibility, making it the go-to standard for microcontroller and small microprocessor applications among leading global enterprises. With a wealth of pre-configured demos and IoT reference integrations readily available, users can easily set up their projects without any hassle. This streamlined process allows for rapid downloading, compiling, and quicker market entry. Furthermore, the ecosystem of partners offers a diverse range of options, including both community-driven contributions and professional support, ensuring that users have access to the resources they need for success. As technology continues to evolve, FreeRTOS remains committed to adapting and enhancing its offerings to meet the ever-changing demands of the industry.
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DuinOS
DuinOS is a compact real-time operating system (RTOS) that supports multithreading and is built on the FreeRTOS kernel, designed specifically for boards compatible with Arduino. The project is undergoing a redevelopment using a fresh strategy, currently utilizing FreeRTOS 10 and plans to incorporate ARM Cortex-M technology in the near future; if you are interested in becoming a Beta Tester, please reach out via the project's official website. This initiative aims to enhance the functionality and performance of Arduino platforms significantly.
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