Real-time Processing
Real-time processing is a computing paradigm where data is processed immediately upon arrival, with strict latency requirements typically measured in milliseconds or seconds. It enables systems to respond to events as they happen, rather than in batch intervals, and is essential for applications requiring instant feedback or decision-making. This contrasts with batch processing, which handles data in large, scheduled groups.
Developers should learn real-time processing for building applications that demand low-latency responses, such as financial trading platforms, fraud detection systems, live analytics dashboards, and IoT sensor monitoring. It's crucial in scenarios where delayed processing could lead to missed opportunities, security breaches, or operational inefficiencies, making it a key skill for modern data-intensive and event-driven architectures.