Reading Feature Data for Inference

Feature data can be read for inference using the methods in the following table.

Method	Description
Using the HTTP API	This is the most common method used to read online feature data for inference. The HTTP API provides reads at low latency for single vector lookups.	Docs   Reference
Using the Java client	Use to read online feature data for inference. The client is a wrapper around the HTTP API and implements best practices for response deserialization and concurrent request handling.	Docs   Reference
Using Feature Output Streams	Feature View Output Streams enable your application to subscribe to the outputs of streaming feature pipelines. Feature View Output Streams are designed to be used for asynchronous predictions, where model inference is triggered by newly arriving feature data.	Docs
Using the Python SDK (Method 1)	Use to read batch feature data for offline inference.	Docs   Reference
Using the Python SDK (Method 2)	Use to read online feature data to test inferences. This method is not suitable for production use.	Docs   Reference