Google Cloud Professional Cloud Database Engineer — Question 1

Your ecommerce website captures user clickstream data to analyze customer traffic patterns in real time and support personalization features on your website. You plan to analyze this data using big data tools. You need a low-latency solution that can store 8 TB of data and can scale to millions of read and write requests per second. What should you do?

Answer options

• A. Write your data into Bigtable and use Dataproc and the Apache Hbase libraries for analysis.
• B. Deploy a Cloud SQL environment with read replicas for improved performance. Use Datastream to export data to Cloud Storage and analyze with Dataproc and the Cloud Storage connector.
• C. Use Memorystore to handle your low-latency requirements and for real-time analytics.
• D. Stream your data into BigQuery and use Dataproc and the BigQuery Storage API to analyze large volumes of data.

Correct answer: A

Explanation

The correct answer is A because Bigtable is designed for low-latency and high throughput, which is essential for handling millions of read and write requests per second. Option B is less suitable as Cloud SQL is not optimized for such high scalability, while option C, Memorystore, is more suited for caching than large-scale data storage. Option D, while BigQuery is powerful for analytics, does not directly address the low-latency storage requirement as effectively as Bigtable.