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Answer: 1. Load the data into Cloud Bigtable. 2. Use the event timestamp to create a row key based event.
**A is incorrect** because Cloud Storage is not suited for high-frequency data updates and atomic operations. It's designed for large, unstructured objects, not for consistent data retrieval based on event time. **B is incorrect** as Cloud Filestore, while good for high-performance file storage, isn't optimized for atomic updates and time-based data retrieval. **C is incorrect** because Datastore (Firestore) isn't ideal for high-frequency time-series data; it lacks efficient, consistent querying based on event time. **D is correct** because Cloud Bigtable excels in handling vast amounts of time-series data with low latency. Using the event timestamp for row keys ensures consistent, efficient data retrieval, making it perfect for analyzing vehicle sensor data. [Learn more about Cloud Bigtable](https://cloud.google.com/bigtable).
Author: LeetQuiz Editorial Team
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Imagine you're managing a modern commercial vehicle rental business, where each vehicle is equipped with sensors monitoring various metrics like engine status, distance traveled, and fuel levels. These metrics are crucial for billing customers. The sensors generate a massive amount of data, potentially thousands of events per hour per device. Your system must store each signal individually and ensure data retrieval is consistent based on the event's timestamp. What is the best approach to handle this scenario?
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D
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