What is real-time feature aggregation architecture?

Real-time feature aggregation computes features on streaming data for immediate classification use.

This architecture uses streaming systems like Kafka or Flink to compute rolling statistics such as counts, averages, and window-based features in real time. These features are pushed into low-latency stores like Redis or DynamoDB for immediate inference use. It is critical in fraud detection and ad-tech systems where freshness is essential.