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This page presents an AI-generated summary of a published research paper. The original authors did not write or review this article. [See full disclosure ↓]

RaaS reduced tail latency in storage-disaggregated databases

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Research area:computer-science-ainetworks-cloud

What the study found

The study found that Replay-as-a-Service, or RaaS, reduced long tail latency in storage-disaggregated databases. It also improved overall throughput in the tested system.

Why the authors say this matters

The authors say storage-disaggregated databases are widely used in the cloud because they can improve resource utilization, reduce fragmentation, and allow compute and storage to scale independently. The study suggests RaaS matters because it addresses the long tail latency problem that the authors identify as a significant limitation of this database design.

What the researchers tested

The researchers focused on online transaction processing (OLTP) databases, including systems such as Amazon Aurora, Microsoft Socrates, and Neon. They implemented RaaS in OpenAurora, an open-source storage-disaggregated database based on PostgreSQL, and evaluated it with SysBench.

What worked and what didn't

RaaS reduced P95 tail latency by 40.1% in the experiments reported in the abstract. It also improved overall throughput by 75.9%. The abstract says the approach works by decoupling log replay from the storage engine and using idle or dedicated servers for replay.

What to keep in mind

The available summary does not describe detailed limitations, trade-offs, or conditions under which the results may change. The reported results are from OpenAurora and SysBench, so the abstract does not state whether the same gains would appear in other systems or workloads.

Key points

  • The paper addresses long tail latency in storage-disaggregated databases.
  • RaaS separates log replay from the storage engine and treats it as an independent service.
  • The implementation was tested in OpenAurora, an open-source PostgreSQL-based system.
  • SysBench experiments reported a 40.1% reduction in P95 tail latency.
  • The abstract reports a 75.9% improvement in overall throughput.

Disclosure

Research title:
RaaS reduced tail latency in storage-disaggregated databases
Authors:
Xi Yu Pang, Jianguo Wang
Institutions:
Purdue University West Lafayette, Purdue University West Lafayette
Publication date:
2026-04-02
DOI:
10.1145/3786688
OpenAlex record:
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AI provenance: This post was generated by gpt-5.4-mini (OpenAI). The original authors did not write or review this post.

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