Data Management on Non-Volatile Memory: A Perspective


The large performance gap between main memory and secondary storage accounts for many design decisions of traditional database systems. With the upcoming availability of Non-Volatile Memory (NVM), which has latencies in the same order of magnitude as DRAM, is byte-addressable and persistent, a completely new type of technology is added to the memory stack. This changes some basic assumptions such as slow storage, block granular access, and that sequential accesses are much faster than random accesses. New ideas are therefore needed to efficiently leverage NVM. Although several new approaches can be found in the literature, the exact role of NVM is not yet clear. In this paper, we survey recent work in this area and classify the existing approaches. We focus on two key challenges: (1) integration of NVM into the memory hierarchy and (2) the design of NVM-aware data structures. We contrast the different approaches, highlight their advantages and limitations, and make recommendations.

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    Also known as Persistent Memory (PM), Non-Volatile Random Access Memory (NVRAM), or Storage Class Memory (SCM).


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This work was partially funded by the German Research Foundation (DFG) in the context of the projects “Transactional Stream Processing on Non-Volatile Memory” (SA 782/28) and “Interactive Big Data Exploration on Modern Hardware” (KE401/22) as part of the priority program “Scalable Data Management for Future Hardware” (SPP 2037). Additionally, Alexander van Renen is supported by Fujitsu Laboratories.

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Correspondence to Philipp Götze or Alexander van Renen or Lucas Lersch.

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Götze, P., van Renen, A., Lersch, L. et al. Data Management on Non-Volatile Memory: A Perspective. Datenbank Spektrum 18, 171–182 (2018).

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  • Non-volatile memory
  • Persistent memory
  • Data management
  • Databases