Google Professional Cloud Developer exam dumps

Google Professional Cloud Developer practice question 403 of 481

Professional Cloud Developer. Professional level, Google Cloud. Free question with the correct answer and a full explanation.

Google Professional Cloud Developer Question 403

Single answerGoogle Cloud Platform

You are building a serverless application on Google Cloud that processes real-time user activity data. The application needs to write this data to a storage solution for long-term analytics and read the same data frequently for operational dashboards. Which datastore would best suit this use case?

  1. A

    Cloud Bigtable

  2. B

    Cloud SQL

  3. C

    Cloud Firestore

  4. D

    Cloud Storage

Show answer and explanation

Correct answer: A

Explanation

Cloud Bigtable is specifically designed for high-throughput and low-latency workloads, making it an excellent choice for storing and analyzing real-time user activity data. It can handle large-scale datasets efficiently and supports frequent reads and writes required for operational dashboards. Other options, while useful for different types of workloads, are not optimized for this specific use case.

  • A. Correct.

    Cloud Bigtable is an ideal choice for real-time analytics and operational dashboard use cases as it is optimized for high-throughput, low-latency read and write operations. It is well-suited for storing large datasets like user activity logs.

  • B. Incorrect.

    Cloud SQL is a relational database service that is better suited for structured data and transactional workloads rather than real-time analytics or storing vast amounts of activity data.

  • C. Incorrect.

    Cloud Firestore is a NoSQL document database that is more suitable for applications requiring hierarchical or document-based data structures, not necessarily for large-scale real-time analytics.

  • D. Incorrect.

    Cloud Storage is designed for storing unstructured data like files, images, and backups. It is not optimized for real-time analytics or frequent reads/writes of structured data.

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