Demo Data from EDBT 2026 / reviewers in the wild / expert
Xinji Zhou
dblp:415/9300
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Transaction processing and concurrency control · 50% Distributed and cloud data management · 50% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Transaction processing and concurrency control
concurrency control |
0.9 | 1 | 2025 | Concurrency Control as a Service · Proc. VLDB Endow. 2025 |
Methods — techniques the papers use, named apart from their topics
sharded multi-write OCC · 0.9deterministic conflict resolution · 0.9asynchronous log push-down · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Concurrency Control as a ServiceabstractExisting disaggregated databases separate execution and storage layers, enabling independent and elastic scaling of resources. In most cases, this design makes transaction concurrency control (CC) a critical bottleneck, which demands significant computing resources for concurrent conflict management and struggles to scale due to the coordination overhead for concurrent conflict resolution. Coupling CC with execution or storage limits performance and elasticity, as CC's resource needs do not align with the free scaling of the transaction execution layer or the storage-bound data layer. This paper proposes Concurrency Control as a Service (CCaaS), which decouples CC from databases, building an execution-CC-storage three-layer decoupled database, allowing independent scaling and upgrades for improved elasticity, resource utilization, and development agility. However, adding a new layer increases latency due to the shift in communication from hardware to network. To address this, we propose a Sharded Multi-Write OCC (SM-OCC) algorithm with an asynchronous log push-down mechanism to minimize network communications overhead and transaction latency. Additionally, we implement a multi-write architecture with a deterministic conflict resolution method to reduce coordination overhead in the CC layer, thereby improving scalability. CCaaS is designed to be connected by a variety of execution and storage engines. Existing disaggregated databases can be revolutionized with CCaaS to achieve high elasticity, scalability, and high performance. Results show that CCaaS achieves 1.02–3.11X higher throughput and 1.11–2.75X lower latency than SoTA disaggregated databases. Weixing Zhou, Yanfeng Zhang 0001, Xinji Zhou, Zhiyou Wang, Zeshun Peng, Sihao Li, Huanchen Zhang, Guoliang Li 0001, Ge Yu 0001 |
Proc. VLDB Endow. | 3 |