Google Professional Cloud Developer exam dumps

Google Professional Cloud Developer practice question 198 of 481

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

Google Professional Cloud Developer Question 198

Select 2Google Cloud Platform

You are developing a payment processing system for an e-commerce platform that requires low-latency, high-concurrency transactions and real-time consistency. The platform also requires periodic reporting on sales trends and customer behavior. Which of the following solutions would best meet these requirements?

  1. A

    Use Cloud Spanner for the payment processing system and BigQuery for the reporting system.

  2. B

    Use BigQuery for both the payment processing and reporting systems.

  3. C

    Use Firestore for the payment processing system and Cloud SQL for the reporting system.

  4. D

    Use Cloud SQL for the payment processing system and BigQuery for the reporting system.

  5. E

    Use Cloud Bigtable for the payment processing system and Cloud Spanner for the reporting system.

Show answer and explanation

Correct answers: A, D

Explanation

The payment processing system requires low-latency, high-concurrency, and strong consistency, which are characteristics of OLTP workloads. Cloud Spanner and Cloud SQL are well-suited for these requirements. The reporting system requires analyzing large datasets and identifying trends, which are characteristics of OLAP workloads. BigQuery is specifically optimized for data warehousing and analytics, making it the ideal choice. Depending on the scale and requirements, either Cloud Spanner and BigQuery or Cloud SQL and BigQuery can fulfill the described use case.

  • A. Correct.

    Cloud Spanner is a highly scalable, strongly consistent database suitable for OLTP workloads like payment processing. BigQuery is an excellent choice for data warehousing and analytics, making this combination ideal for the described use case.

  • B. Incorrect.

    BigQuery is optimized for OLAP (online analytical processing) workloads such as large-scale analytics, not OLTP tasks like payment processing. This makes it unsuitable for both parts of the described system.

  • C. Incorrect.

    Firestore is a NoSQL database suitable for scalable applications but does not provide the same level of consistency and transactional support as Cloud Spanner for OLTP. Cloud SQL is not designed for large-scale reporting or data warehousing.

  • D. Correct.

    Cloud SQL is a relational database suitable for OLTP workloads like payment processing, and BigQuery is optimized for OLAP workloads, making this combination a valid solution for the described requirements.

  • E. Incorrect.

    Cloud Bigtable is a NoSQL database optimized for analytical workloads or time-series data, not transactional consistency. Cloud Spanner, while excellent for OLTP, is not the best choice for large-scale data warehousing compared to BigQuery.

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