Professional Data EngineerEnsuring solution qualityHard

A global ride-sharing company is building a new data processing pipeline to analyze driver and rider location data. Due to the massive scale (trillions of records) and the need for extremely low-latency queries (milliseconds) for real-time decision-making (e.g., dynamic pricing, driver matching), a traditional relational database or standard data warehouse is insufficient. The data is primarily time-series, with new data constantly appended and historical data frequently accessed. You need to select a Google Cloud database service that can handle this scale and performance requirement. Which service is most appropriate?

  1. ACloud Spanner.
  2. BCloud SQL.
  3. CCloud Bigtable.
  4. DBigQuery.
Show answer & explanation

Correct answer: C. Cloud Bigtable.

Cloud Bigtable is a fully managed, NoSQL wide-column database service designed for massive scale (petabytes of data) and extremely low-latency reads and writes (milliseconds). It is particularly well-suited for time-series data, operational analytics, and high-throughput applications where real-time performance on large datasets is critical, making it ideal for the described scenario.

Why the other options are wrong

  • A. Cloud Spanner is a globally distributed, strongly consistent relational database, offering high availability and scalability, but its primary use case is transactional workloads requiring strong consistency, not typically for 'trillions of records' of time-series data with millisecond operational analytical queries, where Bigtable excels.
  • B. Cloud SQL is a relational database and cannot handle 'trillions of records' with 'millions of events per second' and 'milliseconds' latency for operational queries.
  • D. BigQuery is a highly scalable data warehouse for analytical queries, but its latency is typically in seconds, not milliseconds, and it's not optimized for operational, record-level lookups at this scale with millisecond latency.

Cloud Bigtable for Time-Series Data

A fully managed, NoSQL wide-column database optimized for massive-scale time-series, operational, and analytical workloads requiring low-latency reads/writes.

  • Massive scale (petabytes).
  • Extremely low latency (milliseconds).
  • Ideal for time-series and operational analytics.
  • High throughput for reads and writes.

Memory trick: For trillions of records and millisecond queries, Bigtable is your giant, super-fast spreadsheet for real-time decisions.

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