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Real-time data processing is the execution of data in a short time period, providing near-instantaneous output. The processing is done as the data is inputted, so it needs a continuous stream of input data in order to provide a continuous output. Good examples of real-time data processing systems are bank ATMs, traffic control systems and modern computer systems such as the PC and mobile devices. In contrast, a batch data processing system collects data and then processes all the data in bulk in a later time, which also means output is received at a later time.
Real-time data processing is also known as stream processing.
A real-time data processing system is able to take input of rapidly changing data and then provide output near instantaneously so that change over time is readily seen in such a system. For example, a radar system depends on a continuous flow of input data which is processed by a computer to reveal the location of various aircraft flying within the range of the radar and then display it on a screen so that anyone looking at the screen can know the actual location of an aircraft at that moment.
Real-time data processing is also called stream processing because of the continuous stream of input data required to yield output for that moment. Good examples are e-commerce order processing, online booking and reservations, and credit card real-time fraud detection. The biggest benefit of real-time data processing is instantaneous results from input data that ensures everything is up to date. Batch processing, on the other hand, means that data is no longer timely.