Professional Data EngineerDesigning data processing systemsHard
A large retail company needs to migrate its on-premises operational analytics database to Google Cloud. This database handles millions of transactions per second, requires extremely low-latency reads and writes (single-digit milliseconds), and stores data with a simple key-value structure but needs to support complex aggregations and time-series analysis. The data grows to petabytes. Which Google Cloud service is the most appropriate for this workload?
- ACloud Bigtable.
- BCloud Spanner.
- CCloud SQL.
- DBigQuery.
Show answer & explanationAnswer & explanation
Correct answer: A. Cloud Bigtable.
Cloud Bigtable is a petabyte-scale, fully managed NoSQL database service specifically designed for high-throughput, low-latency workloads. Its wide-column store model is ideal for key-value data with complex aggregations and time-series analysis due to its efficient row key design and column family structure. It can handle millions of operations per second with single-digit millisecond latency, making it perfect for operational analytics at this scale.
Why the other options are wrong
- B. Cloud Spanner is a globally distributed relational database, offering strong consistency and high availability, but it's not optimized for the raw throughput and low-latency key-value access patterns of Bigtable, especially for time-series and operational analytics at this scale.
- C. Cloud SQL is a regional relational database and cannot handle millions of transactions per second at petabyte scale with single-digit millisecond latency.
- D. BigQuery is a data warehouse optimized for analytical queries on structured data, not for operational low-latency reads/writes of millions of transactions per second.
Bigtable for Operational Analytics
A fully managed, petabyte-scale NoSQL wide-column database optimized for high-throughput, low-latency operational analytics, suited for time-series and complex aggregations.
- Handles millions of ops/sec with low latency.
- Ideal for time-series and operational data.
- Scales to petabytes of data.
Memory trick: Bigtable: Big throughput, Big data, Big analytics.