Professional Data EngineerDesigning data processing systemsEasy
A large e-commerce company needs to store customer order history, which can grow to petabytes of data over time. This data is primarily used for complex analytical queries, such as identifying purchasing trends, customer segmentation, and quarterly sales reporting. The system must be highly scalable, performant for analytical workloads, and cost-effective for storing massive datasets. Which Google Cloud service is the most appropriate for this data warehousing requirement?
- ACloud Spanner
- BCloud Bigtable
- CCloud SQL
- DBigQuery
Show answer & explanationAnswer & explanation
Correct answer: D. BigQuery
BigQuery is a fully managed, serverless enterprise data warehouse designed for petabyte-scale analytical queries. Its architecture is optimized for complex SQL queries over massive datasets, making it highly scalable, performant, and cost-effective for storing and analyzing customer order history for an e-commerce company.
Why the other options are wrong
- A. Cloud Spanner is a globally distributed, strongly consistent relational database, but it's optimized for transactional workloads requiring global consistency, not primarily for cost-effective petabyte-scale analytical warehousing.
- B. Cloud Bigtable is a NoSQL wide-column store designed for high-throughput, low-latency operational data, not for complex analytical queries on petabytes of structured data.
- C. Cloud SQL is a relational database for transactional workloads, not designed for petabyte-scale analytical data warehousing.
BigQuery for Petabyte-scale Data Warehousing
A serverless, highly scalable, and cost-effective enterprise data warehouse designed for petabyte-scale analytics, offering robust security and compliance features for complex analytical queries.
- Fully managed and serverless.
- Scales automatically to petabytes.
- Optimized for analytical queries (OLAP).
- Cost-effective for massive datasets (storage and query pricing models).
Memory trick: For a mountain of sales data, you need a 'Big Query' to find the gold, not a small shovel.