ITTIA DB SQL is now available for the QNX Neutrino Real-time Operating System (RTOS). ITTIA DB SQL is a database for special-purpose systems that require self-contained data management software. A free evaluation of ITTIA DB SQL for the QNX Neutrino RTOS is available now. The evaluation kit contains a complete embedded database library, optional server, support for both on-disk and in-memory data management and SQL tools.
QNX operating system technology is designed for embedded systems running on ARM, MIPS, Power, SH and x86 platforms. The combination of ITTIA DB SQL and the QNX Neutrino RTOS offers ease of development, maturity, and development time and cost savings for embedded developers.
The QNX Neutrino RTOS and ITTIA DB SQL work together to meet the resource constraints required for embedded systems. QNX Neutrino achieves high performance on embedded processors through an efficient architecture and a field-hardened realtime scheduler. ITTIA DB SQL accelerates storage access with smart I/O buffer management that uses only as much memory as the design can spare. The same RTOS, SDKs, tools, and APIs are used to meet all manner of requirements.
The QNX Neutrino RTOS microkernel allows failed processes — including applications, drivers and protocol stacks — to be restarted without affecting other system components. ITTIA DB SQL ensures that critical data is not lost or corrupted when a task fails, no matter what it is doing when the failure occurs. Together, QNX Neutrino and ITTIA make it possible to build robust, self-healing systems.
QNX Neutrino RTOS support bound multiprocessing (BMP), which is an advanced form of symmetric multiprocessing (SMP). The mission-critical RTOS enables developers to control exactly where each task will run on a multicore chip. When several of these tasks need to access the same database file, ITTIA DB SQL automatically protects each task against write operations in other tasks, on a row-by-row basis. Multi-threaded applications are easy to build, so developers get the full benefit of multicore processing.