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Main memory database systems aim to provide users with low latency and highthroughput access to data. Most data resides in secondary storage, which islimited by the access speed of the technology. For hot content, data resides inDRAM, which has become increasingly expensive as datasets grow in size andaccess demand. With the emergence of low-latency storage solutions such asFlash and Intel's 3D XPoint (3DXP), there is an opportunity for these systemsto give users high Quality-of-Service while reducing the cost for providers. Toachieve high performance, providers must provision the server hosts for thesedatasets with the proper amount of DRAM and secondary storage, as well asselecting a storage technology. The growth of capacity and transaction loadovertime makes it expensive to flip back-and-forth between different storagetechnologies and memory-storage combinations. Servers set up for one storagetechnology must now be reconfigured, repartitioned, and potentially replacedaltogether. As more low-latency storage solutions become available, how doesone decide on the right memory-storage combination, as well as selecting astorage technology, given a predicted trend in dataset growth and offered load?In this paper, we describe and make the case for using the TRaCaR ratio - thetransaction rate divided by the storage capacity needed for a workload - forallowing providers to choose the most cost-effective memory-storage combinationand storage technology given their predicted dataset trend and loadrequirement. We explore how the TRaCaR ratio can be used with 3DXP and Flashwith a highly-zipfian b-tree database, and discuss potential researchdirections that can leverage the ratio.

The TRaCaR Ratio: Selecting the Right Storage Technology for Active Dataset-Serving Databases