Rowsbut

Rowsbut is a term that appears in niche discussions of data processing and database internals. In these contexts, rowsbut refers to a proposed pattern or philosophy of organizing and processing data primarily by rows to improve locality, cache efficiency, and vectorized execution on modern hardware. The term is not part of formal standards and has no widely agreed-upon formal definition.

Origins and usage of rowsbut are diffuse, with appearances in a handful of blog posts, exploratory papers, and talks since the early 2020s. It is not a mainstream concept and lacks a consensus community endorsement or a canonical implementation. As a result, descriptions of rowsbut vary and are often contextual to the author’s workload assumptions.

Conceptually, a rowsbut approach emphasizes preserving row contiguity across processing stages and favoring row-oriented access patterns within analytic or transactional pipelines. Proponents argue that, for certain workloads, row-focused processing can reduce pointer chasing and leverage modern CPU caches and vector units more effectively than strictly column-oriented layouts. Critics note that many analytical tasks benefit from columnar storage and compression, so rowsbut is not universally advantageous and may be workload-dependent.

Relation to other models includes comparisons with row-store and column-store architectures, as well as hybrid and adaptive storage designs. While rowsbut remains a speculative or exploratory concept rather than a standardized method, it contributes to ongoing discussions about how best to structure data pipelines for performance on contemporary hardware. Related terms include row-store, column-store, and vectorized execution.