What term describes low-latency data retrieval of small batches of data for real-time processing?

The term that describes low-latency data retrieval of small batches of data for real-time processing is online serving. Online serving involves the immediate availability of data, enabling applications to retrieve information in real-time or near real-time for various purposes, such as serving predictions in machine learning models or providing instantaneous responses to user queries.

In online serving, the focus is on minimizing response time and ensuring that small chunks of data can be accessed quickly. This is particularly important in scenarios where rapid decisions must be made based on up-to-date information, such as in recommendation systems, fraud detection, or any application requiring instant feedback.

The other options do not match the definition as closely. Batch serving refers to processing large volumes of data at scheduled intervals, typically not focusing on real-time or low-latency needs. Event streaming entails the continuous flow of data events that can be processed in real-time, but it is more about the continuous nature of data flow rather than retrieval for low-latency demands. Data mining is a process focused on discovering patterns in large datasets, which is not typically associated with immediate data retrieval for real-time processing.