How does SAP HANA handle data compression?

SAP HANA employs advanced data compression techniques to optimize storage and improve performance. One of the key methods it utilizes is dictionary encoding, which replaces repeated values with shorter representations, significantly reducing the amount of data stored. This is especially effective for columns with low cardinality where many identical values exist. In addition, run-length encoding is used, which compresses sequences of repeated values into a single value and a count, allowing for further space savings.

The combination of dictionary and run-length encoding is particularly suited for in-memory databases like SAP HANA, where the efficient storage of data directly influences read and write speeds. This dual approach allows SAP HANA to achieve high levels of compression while maintaining performance, particularly when querying large datasets.

Other options, such as binary serialization, zip compression algorithms, and traditional gzip methods, do have their own use cases and benefits but are not the primary techniques employed by SAP HANA for data compression. These alternatives are not as optimized for the in-memory architecture and operational needs specific to SAP HANA, which focuses on real-time data processing and quick access.