Event Stream Processing
Event Stream Processing (ESP) is a computing paradigm that involves continuously analyzing and processing high-volume, real-time data streams as events occur. It enables systems to detect patterns, derive insights, and trigger actions immediately, rather than storing data first for batch processing. ESP is commonly used in applications requiring low-latency responses, such as fraud detection, IoT monitoring, and financial trading.
Developers should learn ESP when building systems that need real-time analytics, immediate decision-making, or handling of high-velocity data streams. It is essential for use cases like monitoring sensor data in IoT, detecting anomalies in cybersecurity, and processing transactions in financial services to enable rapid responses. ESP helps reduce latency and improve system responsiveness compared to traditional batch processing methods.