Real-Time Processing refers to the instantaneous processing of data as it is generated or received. Real-time processing systems, such as those in financial trading platforms, industrial control systems, and IoT (Internet of Things) applications, must meet stringent speed requirements to ensure data is analyzed and acted upon immediately. This type of processing is essential for applications where timely responses are critical to performance or safety.

Characteristics of real-time processing include:

Low Latency: Systems must process data within milliseconds or microseconds, enabling immediate actions based on incoming data.
Continuous Data Flow: Real-time processing typically involves constant data inputs, which are handled in an unbroken flow to maintain up-to-date insights.
High Reliability: Real-time systems must consistently meet performance requirements without delays or interruptions, as delays could lead to operational risks or data inaccuracies.
Examples of real-time processing applications include stock market analysis, emergency response systems, gaming, and health monitoring. These systems require robust infrastructures, such as real-time databases, low-latency networks, and specialized software architectures, to achieve optimal performance.