Skip to main content
Log in

High-availability in-memory key-value store using RDMA and Optane DCPMM

  • Letter
  • Published:
Frontiers of Computer Science Aims and scope Submit manuscript

Conclusion

In this paper, we propose a fast high-availability in-memory key-value store based on RDMA network and Optane DCPMM named FaHA. FaHA proposes RDMA persist PRC that enables remote data persistence for fast log shipping with minimal round-trip and persistence overhead. FaHA further designs append-only storage with pipeline batching scheme in NVM and a hotness-aware differential hash index in DRAM to relieve read/write amplification of Optane DCPMM. Evaluations show that FaHA supports up to 2–3 synchronous backups without significantly lowering the primary’s performance, and outperforms existing works.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

References

  1. Wang T, Johnson R, Pandis I. Query fresh: log shipping on steroids. Proceedings of the VLDB Endowment, 2017, 11(4): 406–419

    Article  Google Scholar 

  2. Yang J, Kim J, Hoseinzadeh M, Izraelevitz J, Swanson S. An empirical guide to the behavior and use of scalable persistent memory. In: Proceedings of the 18th USENIX Conference on File and Storage Technologies. 2020, 169–182

  3. Cooper B F, Silberstein A, Tam E, Ramakrishnan R, Sears R. Benchmarking cloud serving systems with YCSB. In: Proceedings of the 1st ACM Symposium on Cloud Computing. 2010, 143–154

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Huiqi Hu.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qi, X., Hu, H., Guo, J. et al. High-availability in-memory key-value store using RDMA and Optane DCPMM. Front. Comput. Sci. 17, 171603 (2023). https://doi.org/10.1007/s11704-022-1123-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11704-022-1123-8

Navigation