The granularity of concurrency control has a big impact on the performance of transactional systems. Concurrency control granu- larity and data granularity (data size) are usually the same. The e ect of this coupling is that if a coarse granularity is used, the overhead of data access (number of disk accesses) is reduced, but also the degree of concurrency. On the other hand, if a ne granularity is chosen to achieve a higher degree of concurrency (there are less con icts), the cost of data access is increased (each data item is accessed independently, which increases the number of disk accesses). There have been some pro- posals where data can be dynamically clustered/unclustered to increase either concurrency or data access depending on the application usage of data. However, concurrency control and data granularity remain tightly coupled. In Transactional Drago, a programming language for building distributed transactional applications, concurrency control has been un- coupled from data granularity, thus allowing to increase the degree of concurrency without degrading data access. This paper describes this approach and its implementation in Ada 95.