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Modern high-performance computing systems and databases are implemented under the assumption that a very large proportion of the data used can now be maintained in volatile memory. In this paper, we compare experimentally two recently proposed self-adjusting access structures that can be used to organize data in such settings, namely, the Skip-List (SL) and the Binary B-Tree (BB-Tree). We examine the scalability of these two methods against both mixed and pure-query workloads. Our experimentsdoi:10.1093/comjnl/40.4.183 fatcat:xdhrmhn5azacriigc7vwguadve