What happens to the data footprint when using column store tables in SAP HANA?

When using column store tables in SAP HANA, the data footprint is automatically reduced through compression. This is a fundamental feature of column-oriented storage, where data is stored in columns rather than rows. Since column store tables often contain similar data types within each column, they can leverage advanced compression techniques more effectively. These techniques include dictionary encoding and run-length encoding, among others, allowing for a significantly smaller physical storage footprint compared to traditional row-oriented systems.

The ability to compress data efficiently in columnar formats not only reduces the required storage space but also enhances performance for analytical queries. This is because less data needs to be scanned from the disk, allowing for faster access and improved response times for retrieving aggregated or filtered data. Hence, the correct answer highlights the automatic reduction of the data footprint through these compression techniques in SAP HANA's column store architecture.