Real-Time Stream Processing

For time-sensitive applications, real-time processing frameworks such as Apache Flink and Apache Storm are used to analyze streaming data. These systems process event-driven data streams in low-latency environments, enabling use cases like fraud detection, anomaly detection, and real-time monitoring. Message brokers like Apache Kafka ensure efficient message queuing and data flow management.