MQX RTOS Description
The MQX real-time operating system (RTOS) delivers excellent real-time capabilities while maintaining a compact and customizable footprint. This RTOS is seamlessly integrated with NXP's 32-bit MCUs and MPUs and comes with essential device drivers commonly utilized in embedded applications. Designed with a contemporary, component-oriented microkernel architecture, the MQX RTOS allows engineers to tailor features, size, and performance by selectively integrating components, thus adhering to the stringent memory limitations typical of embedded systems. Remarkably, it can be set up to use as little as 8 KB of ROM and 2.5 KB of RAM on the Arm Cortex M4, accommodating the kernel, two task applications, one lightweight semaphore, the interrupt stack, queues, and the memory manager. This configuration ensures a complete RTOS core is available while offering additional optional services as needed. By linking components only when required, the system effectively avoids unnecessary memory bloat from unused functions. Moreover, key components are offered in both standard and lightweight configurations, providing further flexibility regarding size, RAM and ROM usage, and performance options, making it a versatile choice for various applications.
MQX RTOS Alternatives
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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Google Compute Engine
Compute Engine (IaaS), a platform from Google that allows organizations to create and manage cloud-based virtual machines, is an infrastructure as a services (IaaS).
Computing infrastructure in predefined sizes or custom machine shapes to accelerate cloud transformation. General purpose machines (E2, N1,N2,N2D) offer a good compromise between price and performance. Compute optimized machines (C2) offer high-end performance vCPUs for compute-intensive workloads. Memory optimized (M2) systems offer the highest amount of memory and are ideal for in-memory database applications. Accelerator optimized machines (A2) are based on A100 GPUs, and are designed for high-demanding applications. Integrate Compute services with other Google Cloud Services, such as AI/ML or data analytics. Reservations can help you ensure that your applications will have the capacity needed as they scale. You can save money by running Compute using the sustained-use discount, and you can even save more when you use the committed-use discount.
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Zephyr
Ranging from basic embedded environmental sensors and LED wearables to advanced embedded controllers, smartwatches, and IoT wireless applications, this system incorporates configurable architecture-specific stack-overflow protection, kernel object and device driver permission tracking, and thread isolation enhanced by thread-level memory protection across x86, ARC, and ARM architectures, as well as userspace and memory domains. For systems lacking MMU/MPU and those limited by memory capacity, it enables the integration of application-specific code with a tailored kernel to form a monolithic image that can be loaded and run on the hardware of the system. In this setup, both the application and kernel code operate within a unified address space, facilitating efficient resource utilization and performance optimization. This design ensures that even resource-constrained environments can effectively leverage complex applications and functionalities.
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QNX Neutrino RTOS
Since its inception in 1980, QNX has been the choice of thousands of enterprises seeking to implement real-time operating systems that deliver an optimal blend of performance, security, and reliability for their mission-critical operations. Central to QNX's innovation is the QNX Neutrino® Real-time Operating System (RTOS), which is a comprehensive solution that facilitates the development of next-generation products across various sectors where dependability is paramount, such as automotive, healthcare devices, robotics, transportation, and industrial embedded environments. Thanks to its microkernel architecture, QNX ensures that a failure in one component does not disrupt the operation of others or compromise the kernel, as the malfunctioning part can be simply halted and restarted without negatively impacting the overall system. The QNX Neutrino RTOS stands out by providing the determinism unique to real-time operating systems, employing methods like adaptive partitioning to ensure that essential processes receive the necessary processing cycles to perform their tasks promptly, all while sustaining the performance expectations of intricate embedded systems. This combination of features makes QNX Neutrino RTOS a preferred choice for developers looking to create robust and resilient applications. As technology continues to evolve, the adaptability of QNX's offerings ensures that they remain at the forefront of real-time operating system solutions.
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Company Details
Company:
NXP
Year Founded:
2006
Headquarters:
Netherlands
Website:
www.nxp.com/design/software/embedded-software/mqx-software-solutions/mqx-real-time-operating-system-rtos:MQXRTOS
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Linux
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