What database architecture should you use for time-series, transactional, and historical query workloads?
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Correct answer: Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery for historical data queries..
Why this is the answer
This option correctly matches each workload type with the most suitable Google Cloud database service. Cloud Bigtable is ideal for time-series data due to its high throughput and low latency for large analytical and operational workloads. Cloud Spanner is a globally distributed, strongly consistent relational database perfect for transactional data requiring high availability and horizontal scalability. BigQuery is a serverless, highly scalable data warehouse designed for cost-effective historical data analysis and complex queries. The other options either misassign services (e.g., Cloud SQL for time series or historical data) or suggest replacing a relational database like MySQL with a NoSQL database (Bigtable) without considering the transactional requirements.
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