QuestionQ82
Custom Model ServingA Machine Learning Engineer is developing an application that needs low-latency data lookups in response to a user’s question after a RAG-based search. They want to ensure users receive the most recent data possible for urgent requests, so the data must be no more than a few minutes late. The underlying data is a large table that can contain hundreds of gigabytes of data.
Which data-serving approach best suits this use case?
- A Online tables with snapshot sync mode
- B A fast database hosted in MLflow model serving
- C Online tables with continuous sync mode
- D Online tables with triggered mode and a time series key
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