easyMultiple Choice
MLA-C01 Practice Question: A data engineer is building a feature store using…
A data engineer is building a feature store using Amazon SageMaker Feature Store. The team needs to store features that are updated frequently and require low-latency retrieval for real-time inference. Which type of store should the engineer use?
⚠ Common exam trap
MLA-C01 often tests the confusion between online and offline stores; candidates mistakenly select the offline store because it sounds more comprehensive, but the offline store is for batch, not low-latency real-time inference.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Online store
The online store in Amazon SageMaker Feature Store is designed for low-latency, real-time retrieval of feature values for inference. It is backed by a low-latency storage layer and supports single-digit millisecond reads, which is exactly what real-time inference requires. The offline store, by contrast, is optimized for batch training and historical lookups, not real-time serving.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Both online and offline store
Why it's wrong here
Configuring both stores adds an offline S3 copy that real-time inference never reads, so it does not satisfy the low-latency requirement alone. It is tempting because it supports training and serving together, and would be right when historical features are also needed.
- ✗
Offline store
Why it's wrong here
The offline store serves batch reads from S3 for training, not low-latency real-time inference, so it fails the latency requirement. It is tempting because it retains full feature history, and would be correct for training datasets or batch scoring rather than online serving.
- ✓
Online store
Why this is correct
The online store serves features at millisecond latency for real-time inference, satisfying the low-latency retrieval constraint. It is backed by a low-latency online database, whereas the offline store holds historical data in Amazon S3 for training and batch scoring, not real-time serving.
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Amazon DynamoDB directly
Why it's wrong here
DynamoDB stores raw items but provides no feature-group schema, online/offline synchronisation, or Feature Store retrieval APIs, so it is not a feature store. It is tempting because it offers low-latency key-value reads, and would be correct for a custom-built serving table.
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Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.