A system needs to store and query time-series data from 1000 sensors, generating 1 metric/sensor/second. Existing data is 1TB, growing at 1GB/day. Two access patterns exist: (1) Retrieving a single sensor's metric at a specific timestamp (single-digit millisecond latency required); (2) Daily complex analytics queries (including joins).
The suggested answer is B. Bigtable excels at low-latency point lookups due to its row-key based design. Using concatenated sensor ID and timestamp as the row key allows for fast retrieval of individual sensor data at a given timestamp. Daily export to BigQuery enables efficient execution of complex analytics queries.
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