Structure of database with billions of rows of data
This is a typical way to deal with this kind of data.

If you had a postgres database, you'd create one master table (to formalize the structure of the sensor data), and then create tables that inherit all the columns from the master table without adding any additional columns. This would create a partitioning of your data based on date / timestamp of the sensor data. 

Querying the master table in this configuration means going through all the child tables and returning the approapriate answers. If one adds the "check" constraints for the child tables (corresponding to the temporal data in the tables), only the relevant children will be scanned.

See more e.g., https://www.postgresql.org/docs/10/static/ddl-partitioning.html

SQL Server 2014 seems to have a similar concept:

https://docs.microsoft.com/en-us/sql/relational-databases/partitions/create-partitioned-tables-and-indexes