With the advent of real-time and goal-oriented database systems, priority scheduling is likely to be an important feature in future database management systems. A consequence of priority scheduling is that a transaction may lose its buffers to higher-priority transactions, and may be given additional memory when transactions leave the system. Due to their heavy reliance on main memory, hash joins are especially vulnerable to fluctuations in memory availability. Previous studies have proposed modifications to the hash join algorithm to cope with these fluctuations, but the proposed algorithms have not been extensively evaluated or compared with each other. This paper contains a performance study of these algorithms. In addition, we introduce a family of memory-adaptive hash join algorithms that turns out to offer even better solutions to the memory fluctuation problem that hash joins experience.