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A manufacturing company uses thousands of IoT sensors to monitor machine performance on its factory floor. These sensors generate high volumes of time-series data (e.g., temperature, pressure, vibration) at sub-second intervals. The company needs a database that can handle extremely high write and read throughput for this type of data, specifically for operational analytics and real-time dashboards. Which Google Cloud database is best suited for this use case?
- ACloud SQL
- BCloud Bigtable
- CCloud Spanner
- DFirestore
Show answer & explanationAnswer & explanation
Correct answer: B. Cloud Bigtable
Cloud Bigtable is a fully managed, scalable NoSQL wide-column database service specifically designed for large analytical and operational workloads, including IoT time-series data. It excels at handling very high read/write throughput and low-latency access, making it ideal for real-time sensor data.
Why the other options are wrong
- A. Cloud SQL is a relational database, not designed for the extreme write/read throughput of IoT time-series data.
- C. Cloud Spanner is a globally distributed relational database, optimized for transactional consistency, not the high-volume, low-latency needs of IoT time-series.
- D. Firestore is a NoSQL document database, better suited for mobile/web apps and less for extreme time-series throughput.
Cloud Bigtable
A fully managed, scalable NoSQL wide-column database service designed for large analytical and operational workloads, including IoT and time-series data.
- Handles extremely high read/write throughput.
- Low-latency access.
- Ideal for time-series data, IoT, and operational analytics.
Memory trick: Bigtable handles Big Time-Series data.