Explanation:
The correct answer is A: Create a multi-region Cloud Spanner instance with an optimized schema. Cloud Spanner is designed to handle large volumes of global transactions and provides a highly available and scalable solution. It supports SQL queries for analysis, making it an ideal choice for the requirements described in the question. Cloud Spanner's multi-region capabilities ensure that the data is highly available across different locations, and its support for relational schema and SQL queries makes it suitable for transaction data analysis.
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You are tasked with developing a backend service for an ecommerce platform designed to store transaction data received from both mobile and web clients. Following the launch, you anticipate handling a significant volume of transactions from users all around the world. The business team requires the capability to perform SQL queries for data analysis purposes. Your objective is to create a data store that is both highly available and scalable for the platform. What action should you take?
A
Create a multi-region Cloud Spanner instance with an optimized schema.
B
Create a multi-region Firestore database with aggregation query enabled.
C
Create a multi-region Cloud SQL for PostgreSQL database with optimized indexes.
D
Create a multi-region BigQuery dataset with optimized tables.