You need petabyte-scale aggregations and millisecond-range row scans over time-series telemetry. Which product pair satisfies both use cases?

BigQuery is ideal for petabyte-scale aggregations due to its columnar storage and massively parallel processing capabilities, making it excellent for analytical queries over large datasets. Cloud Bigtable excels at millisecond-range row scans for time-series data because it's a wide-column NoSQL database designed for low-latency reads and writes on massive datasets, especially suitable for time-series and IoT data. Cloud Datastore is a document database, not optimized for petabyte-scale aggregations or time-series row scans. Cloud SQL is a relational database, not designed for petabyte-scale data or the low-latency, high-throughput demands of time-series row scans. Cloud Storage is object storage, not a database, and thus not suitable for direct querying or row scans.