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In the past, the common assumption was that main memory would become cheap and abundant enough to power database systems solely. This assumption did not hold. This chapter presents approaches on how modern database systems can scale beyond a single server’s main memory capacity by utilizing trends in modern hardware without sacrificing performance. To this end, we present four systems: Mosaic, a storage engine for analytical workloads; Plush, a PMem-optimized storage structure for transactional workloads; PMFDS, a novel programming model for fully disaggregated systems; and finally, FireArm, a just-in-time compilation framework for rising ARM systems in the server space.

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Scaling Beyond DRAM Without Compromising Performance

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Lukas Vogel,
  • Christoph Anneser,
  • Ferdinand Gruber,
  • Thomas Neumann,
  • Jana Giceva,
  • Alfons Kemper

摘要

In the past, the common assumption was that main memory would become cheap and abundant enough to power database systems solely. This assumption did not hold. This chapter presents approaches on how modern database systems can scale beyond a single server’s main memory capacity by utilizing trends in modern hardware without sacrificing performance. To this end, we present four systems: Mosaic, a storage engine for analytical workloads; Plush, a PMem-optimized storage structure for transactional workloads; PMFDS, a novel programming model for fully disaggregated systems; and finally, FireArm, a just-in-time compilation framework for rising ARM systems in the server space.