To store large-scale historical time-series data with efficient querying and CMEK encryption, what is the most appropriate approach?

*The optimal solution for storing large-scale historical time-series data with the requirement for efficient querying and encryption using Customer-Managed Encryption Keys (CMEK) is BigQuery with Partitioned Tables and CMEK. BigQuery is a powerful and scalable data warehouse service that excels in handling large volumes of time-series data. Its support for partitioned tables allows for efficient querying and management of large datasets by dividing them into smaller, manageable segments based on specified criteria such as time. The integration of CMEK with BigQuery enables users to use their encryption keys, providing an additional layer of security and control over their data. This setup meets the requirements of handling extensive time-series data, offering efficient data processing capabilities and adherence to encryption and security needs. Other options, like Cloud Bigtable or Cloud SQL, either do not support CMEK or are not optimized for large-scale time-series data handling and querying.*