A Write-Optimized Distributed B+Tree Index on Disaggregated Memory

Abstract

If it were possible to scale memory independently from compute, it would be feasible to dynamically adjust the amount of memory based on the workload. It would further enable better resource utilization. Consider a dynamic workload regarding the number of queries but with very strict response time requirements, which can only be met, if data is kept in-memory. In this case, the separation of compute and memory would enable to scale the compute with the number of queries while keeping all the data constantly in-memory. This design principle is already used by services such as Google, which keeps the entire web-index in-memory.