docs/getting-started/concepts/stream-feature-view.md
StreamFeatureView is a type of feature view in Feast that allows you to define features that are continuously updated from a streaming source. It is designed to handle real-time data ingestion and feature generation, making it suitable for use cases where features need to be updated frequently as new data arrives.
Real-time Feature Generation: Supports defining features that are continuously updated from a streaming source.
Transformations: Apply transformation logic (e.g., feature_transformation or udf) to raw data source.
Aggregations: Define time-windowed aggregations (e.g., sum, avg) over event-timestamped data.
⚡ Tiling with Intermediate Representations: Enable efficient pre-aggregation with correct merging semantics for holistic aggregations like avg and std. This provides faster queries while maintaining mathematical accuracy. Learn more about tiling
Feature resolution & execution: Automatically resolves and executes dependent views during materialization or retrieval.