Google-recommended Tool

D.

The Google-recommended tool for building an online analytical processing (OLAP) marketing analytics and reporting tool that requires a relational database capable of operating on hundreds of terabytes of data is BigQuery.

BigQuery is a fully-managed, cloud-native data warehouse that enables users to run complex analytical queries on large datasets. It is a serverless platform that does not require any infrastructure management or maintenance, and it provides high performance and scalability for handling massive amounts of data.

BigQuery uses a columnar storage format that enables fast query processing and high compression rates, which reduces storage costs. Additionally, BigQuery has built-in machine learning capabilities that enable users to build and train machine learning models on their data within the platform.

In contrast, Cloud Spanner is a globally distributed, horizontally scalable relational database service that provides strong consistency and high availability. It is designed to support large-scale transactional workloads, but it is not optimized for OLAP workloads.

Cloud SQL is a fully managed relational database service that provides a familiar SQL interface and is designed for small to medium-sized workloads. It may not be able to handle the scale of hundreds of terabytes of data required for an OLAP system.

Cloud Firestore is a flexible, scalable, and fully managed NoSQL document database service that offers real-time synchronization across devices. While it can be used for data analytics, it is not optimized for OLAP workloads and may not be able to handle the scale of hundreds of terabytes of data.

In summary, BigQuery is the Google-recommended tool for building an OLAP marketing analytics and reporting tool that requires a relational database capable of operating on hundreds of terabytes of data. It is a fully-managed, cloud-native data warehouse that provides high performance, scalability, and built-in machine learning capabilities.