Ziegler, Tobias ; Binnig, Carsten ; Leis, Viktor
Hrsg.: Ives, Zachary ; Bonifati, Angela ; Abbadi, Amr El (2022)
ScaleStore: A Fast and Cost-Efficient Storage Engine using DRAM, NVMe, and RDMA.
SIGMOD '22: International Conference on Management of Data. Philadelphia, USA (12.-17.06.2022)
doi: 10.1145/3514221.3526187
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

In this paper, we propose ScaleStore, a novel distributed storage engine that exploits DRAM caching, NVMe storage, and RDMA networking to achieve high performance, cost-efficiency, and scalability at the same time. Using low latency RDMA messages, ScaleStore implements a transparent memory abstraction that provides access to the aggregated DRAM memory and NVMe storage of all nodes. In contrast to existing distributed RDMA designs such as NAM-DB or FaRM, ScaleStore integrates seamlessly with NVMe SSDs, lowering the overall hardware cost significantly. The core of ScaleStore is a distributed caching strategy that dynamically decides which data to keep in memory (and which on SSDs) based on the workload. The caching protocol also provides strong consistency in the presence of concurrent data modifications. In our YCSB-based evaluation, we show that ScaleStore can provide high performance for various types of workloads (read/write-dominated, uniform/skewed) even when the data size is larger than the aggregated memory of all nodes. We further show that ScaleStore can efficiently handle dynamic workload changes and support elasticity.

Frage zum Eintrag

Redaktionelle Details anzeigen