Google Professional Cloud Developer Question 195
Select 2Google Cloud PlatformYour organization is developing a new e-commerce platform that requires real-time processing of customer orders, inventory updates, and payment transactions. You also need to periodically generate business reports summarizing daily sales and customer trends. Which combination of Google Cloud databases would best suit these requirements?
- A
Use Cloud Spanner for real-time transaction processing and BigQuery for generating business reports.
- B
Use Firestore for real-time transaction processing and BigQuery for generating business reports.
- C
Use BigQuery for both real-time transaction processing and business reports.
- D
Use Cloud SQL for real-time transaction processing and Dataflow for generating business reports.
- E
Use Cloud Spanner for both real-time transaction processing and business reports.
Show answer and explanation
Correct answers: A, D
Explanation
This scenario requires a combination of systems optimized for both OLTP and data warehousing. Cloud Spanner is a strong choice for handling real-time transactional processing due to its ACID compliance, scalability, and strong consistency. For generating periodic business reports and analyzing large datasets, BigQuery is the most appropriate tool, as it is a highly scalable data warehousing solution. Cloud SQL could also be used for OLTP, and Dataflow can complement BigQuery by preparing data for analytics, making both combinations valid solutions for the scenario.
- A. Correct.
Cloud Spanner is a globally distributed, horizontally scalable, strongly consistent database that is ideal for online transaction processing (OLTP). BigQuery is optimized for data warehousing and supports analytical queries, making this combination ideal for the given scenario.
- B. Incorrect.
Firestore is suitable for NoSQL use cases and real-time synchronization but is not typically used for OLTP workloads like payment transactions. However, BigQuery is suitable for generating business reports.
- C. Incorrect.
BigQuery is a data warehouse optimized for analytical queries and not suitable for real-time transaction processing. It is not designed to handle OLTP workloads.
- D. Correct.
Cloud SQL is suitable for traditional OLTP workloads like relational database transactions, and Dataflow can be used for ETL (Extract, Transform, Load) pipelines to prepare data for analytics in BigQuery.
- E. Incorrect.
While Cloud Spanner is suitable for OLTP, it is not optimized for data warehousing or analytical queries, which would make it inefficient for generating business reports compared to BigQuery.