Software splits large problems into smaller subtasks and distributes them to different processors, which simultaneously handle the subtasks and so reach a solution faster than a uniprocessor system does. Various trends are driving commercial parallelism. Data in legacy systems is not easily accessible. Multiple-processor architectures have become increasingly fast, scalable and easier to administer. Tools have improved to install and administer the multithreaded operating systems and database engines for these platforms.
Application development is less onerous now.
More than any of these reasons, the driving force is that databases are growing. Databases of 2GB to 3GB, once considered large, are dwarfed by those of 10GB and more. From the hardware perspective, parallel processing is almost a moot question. Database servers increasingly have parallel capability. Many servers that run the Unix operating system house two, four or more CPUs.