The terms rowstore and columnstore have been widely adopted in database management for online transaction processing (OLTP) and online analytical processing (OLAP) workloads, respectively. However, a nuanced approach is required to determine when to use each type of storage based on the specific characteristics of the workload. Rowstores excel at random reads and writes, while columnstores are better suited for sequential reads and writes. Despite common myths, columnstores can be faster than rowstores in certain scenarios, such as workloads with sequential scans or computationally analytic but operationally constrained constraints. Hybrid Transactional/Analytical Processing (HTAP) workloads, which blend both OLTP and OLAP characteristics, often benefit from using a combination of rowstore and columnstore indexes. Ultimately, the choice between rowstores and columnstores depends on the specific requirements of the workload, including the types of operations performed, storage constraints, and performance considerations.