German strings, implemented as StringViews in the Rust Arrow library, have gained traction as a standard for representing string columns due to their simplicity and efficiency in string processing tasks like comparisons, filters, and sorting. However, this encoding method can be memory-intensive, as each element requires a 16-byte representation, which is not always optimal for all use cases, such as those with low-cardinality string columns. At Polar Signals, dictionary encoding has proven more efficient, reducing memory usage by 75% compared to StringViews, since it uses a smaller index buffer tailored to the number of distinct values. This highlights the importance of selecting data encoding methods based on specific workload and storage characteristics rather than defaulting to a one-size-fits-all approach. While dynamic selection of physical encodings during execution and storage is gaining traction, it remains a work in progress, emphasizing the need for database systems to avoid making assumptions about optimal encodings on behalf of users.