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 experiments reveal the behaviour of SLs and BB-Trees under diverse environments and varying data requirements.
ASJC Scopus subject areas
- Computer Science(all)