What is real-time recommendation system architecture?

A real-time recommender updates recommendations instantly based on user actions.

Real-time systems use streaming pipelines (Kafka, Flink) to capture user events and update feature stores or embeddings. A low-latency serving layer retrieves candidates and applies ranking models in milliseconds. This enables dynamic personalization based on latest interactions.