You are tasked with building an online analytical processing (OLAP) marketing analytics and reporting tool. This requires a relational database that can operate on hundreds of terabytes of data. What is the Google-recommended tool for such applications?

BigQuery is the Google-recommended tool for this scenario because it is a fully managed, serverless data warehouse designed for large-scale analytical processing (OLAP) of petabytes of data. Its columnar storage and massively parallel processing (MPP) architecture make it highly efficient for complex queries on vast datasets, perfectly suiting marketing analytics and reporting. Cloud Spanner is a globally distributed, strongly consistent relational database, but it's primarily designed for transactional workloads (OLTP) requiring high availability and horizontal scalability, not optimal for large-scale analytical queries. Cloud SQL is a fully managed relational database service for MySQL, PostgreSQL, and SQL Server, suitable for smaller to medium-sized transactional or operational databases, but it struggles with hundreds of terabytes for OLAP. Cloud Firestore is a NoSQL document database, ideal for mobile, web, and IoT applications requiring real-time data synchronization, not for large-scale analytical reporting on structured tabular data.