Google Exam Professional Cloud Database Engineer Topic 10 Question 14 Discussion

Actual exam question for Google's Professional Cloud Database Engineer exam

Question #: 14
Topic #: 10

[All Professional Cloud Database Engineer Questions]

You are choosing a database backend for a new application. The application will ingest data points from IoT sensors. You need to ensure that the application can scale up to millions of requests per second with sub-10ms latency and store up to 100 TB of history. What should you do?

AUse Cloud SQL with read replicas for throughput.

BUse Firestore, and rely on automatic serverless scaling.

CUse Memorystore for Memcached, and add nodes as necessary to achieve the required throughput.

DUse Bigtable, and add nodes as necessary to achieve the required throughput.

Show Suggested Answer

Suggested Answer: C

by Willard at Feb 07, 2023, 03:45 AM

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Gracia

1 months ago

I'm just picturing the poor database admin trying to keep up with adding Bigtable nodes like a hamster on a wheel. 'Wheee, another node! Wheee, another node!'

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Evelynn

2 days ago

D) Bigtable seems like the best option for handling the required throughput.

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Lavonne

3 days ago

C) Memorystore for Memcached sounds like a good choice for adding nodes as needed.

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Tijuana

8 days ago

B) I think Firestore would be a better option for automatic scaling.

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Kenneth

11 days ago

A) Use Cloud SQL with read replicas for throughput.

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Melodie

1 months ago

Cloud SQL with read replicas? Really? That's like trying to use a bicycle to haul a freight train. This application needs serious big-data firepower, not your grandpa's SQL database.

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Hoa

4 days ago

D) Use Bigtable, and add nodes as necessary to achieve the required throughput.

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Sherron

15 days ago

A) Use Bigtable, and add nodes as necessary to achieve the required throughput.

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Cassie

1 months ago

Ooh, Memorystore for Memcached? That's an interesting idea! But I'm not sure if it can keep up with the insane throughput and data volume this application needs. Definitely not a good fit in my opinion.

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Aileen

2 months ago

I'm not so sure about Bigtable. What about Firestore? It's serverless, so you don't have to worry about scaling it up yourself. And it can probably handle the data volume and throughput requirements.

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Lezlie

6 days ago

D) Use Bigtable, and add nodes as necessary to achieve the required throughput.

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Martina

11 days ago

B) Use Firestore, and rely on automatic serverless scaling.

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Taryn

19 days ago

A) Use Cloud SQL with read replicas for throughput.

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Kristofer

2 months ago

Hmm, I think option D is the way to go. Bigtable can handle massive amounts of data and scale up to millions of requests per second. Plus, it's designed for time-series data like IoT sensor data.

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