You need to choose a database to store time series CPU and memory usage for millions of computers. You need to store this data in one-second interval samples. Analysts will be performing real-time, ad hoc analytics against the database. You want to avoid being charged for every query executed and ensure that the schema design will allow for future growth of the dataset. Which database and data model should you choose?

Options:

A Create a table in BigQuery, and append the new samples for CPU and memory to the table

B Create a wide table in BigQuery, create a column for the sample value at each second, and update the row with the interval for each second

C Create a narrow table in Cloud Bigtable with a row key that combines the Computer Engine computer identifier with the sample time at each second

D Create a wide table in Cloud Bigtable with a row key that combines the computer identifier with the sample time at each minute, and combine the values for each second as column data.

Need a google documentation to justify your solution/ suggestion