Online vs offline feature store architecture and use cases
This tests latency trade-offs between real-time and batch infrastructure. Contrast fast online lookups against batch offline stores; fraud detection maps to online and model training to offline. Red flag: treating them as interchangeable and ignoring latency.
This tests your grasp of latency and consistency trade-offs between production serving and batch training. A strong answer contrasts online stores built for millisecond-scale lookups via in-memory databases against offline stores holding large historical datasets in data lakes. It maps real-time fraud detection and recommendations to online, and model retraining plus batch scoring to offline. A red flag is treating them as interchangeable or calling offline stores merely cheaper alternatives without addressing latency and freshness needs.
Read the original → geeksforgeeks.org
- #mlops
- #feature-store
- #system-design
- #real-time
- #batch-processing
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