PMLE Practice Question: Collaborating Within and Across Teams to Manage Data and Models
A team uses Vertex AI Feature Store with an online store for low-latency serving. They need to support frequent updates to features (e.g., every minute) and require high write throughput (thousands of writes per second). Which online store type should they choose?
⚠ Common exam trap
The trap is assuming that any low-latency online store can handle high write throughput; candidates must distinguish between read-optimized and write-optimized stores, with Bigtable being the only one designed for massive write scalability.
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
✓
Bigtable online store
Bigtable online store is designed for high-throughput, low-latency serving with frequent updates, making it suitable for thousands of writes per second and minute-level feature refreshes. It leverages Bigtable's scalable NoSQL architecture, which handles high write loads efficiently. Optimized online store is for low-latency but may not sustain such high write throughput, while Firestore and Cloud SQL have lower write limits.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Optimized online store
Why it's wrong here
The optimised online store serves low-latency reads but does not sustain thousands of feature writes per second with minute-level freshness; it is designed for read-heavy serving. Bigtable online store is tempting for its low-latency reads, yet only the Bigtable-based option supports the required high write throughput.
- ✗
Firestore online store
Why it's wrong here
Firestore's write throughput per collection is limited, so sustaining thousands of writes per second for minute-level refreshes would throttle or require complex sharding. It is tempting because Firestore offers low-latency reads, which would be correct for read-heavy serving with infrequent feature updates.
- ✓
Bigtable online store
Why this is correct
Bigtable online store supports high write throughput and frequent feature updates, scaling to thousands of writes per second with low-latency reads. This satisfies the stated requirement for minute-level updates and high-throughput ingestion that the default online store cannot match.
- ✗
Cloud SQL online store
Why it's wrong here
Cloud SQL is a relational database whose write throughput and scaling cannot sustain thousands of writes per second for minute-level feature refreshes. It is tempting because it suits low-volume online stores or teams already standardised on relational databases, where update frequency is modest.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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