Professional Data EngineerBuilding and operationalizing data processing systemsHard
A global online gaming company needs to store petabytes of user gameplay data, including session logs, in-game events, and player statistics. This data is characterized by extremely high write throughput (millions of writes per second), low-latency reads for real-time leaderboards and player profiles, and requires horizontal scalability to handle unpredictable traffic spikes. Data consistency is eventually consistent for most use cases, but strong consistency is preferred where possible. Which Google Cloud database service is best suited for this workload?
- ACloud Bigtable
- BCloud SQL
- CBigQuery
- DCloud Spanner
Show answer & explanationAnswer & explanation
Correct answer: A. Cloud Bigtable
Cloud Bigtable is a wide-column NoSQL database designed for very large analytical and operational workloads, offering extremely high write and read throughput at low latency, horizontal scalability, and is ideal for time-series data like gameplay logs.
Why the other options are wrong
- B. Cloud SQL is a relational database not designed for petabytes of data or millions of writes/sec.
- C. BigQuery is an analytical data warehouse, not suitable for low-latency operational reads and writes for individual records.
- D. Cloud Spanner offers strong consistency and horizontal scalability but is typically more expensive and geared towards transactional workloads requiring ACID properties, which are not strictly mandated for all gameplay data here.
Cloud Bigtable
Cloud Bigtable is a fully managed, scalable NoSQL wide-column database service for large analytical and operational workloads, offering high throughput and low latency.
- Ideal for time-series, marketing, financial, and IoT data.
- Supports millions of reads/writes per second.
- Sub-10ms latency for typical operations.
- Horizontally scalable, integrates with Hadoop, Dataflow, etc.
Memory trick: Big gaming data, Bigtable's big speed.