What is feature store online-offline consistency guarantee?

Consistency guarantees ensure identical feature values between training (offline) and inference (online).

Feature stores must ensure that the same computation logic produces identical results in both offline batch pipelines and real-time serving systems. This involves deterministic transformations, versioned feature definitions, and synchronized pipelines. Inconsistencies lead to training-serving skew, which is one of the most common production ML failures.