Demo Data from VLDB 2026 / reviewers in the wild / expert
Zerui Ge
dblp:320/5591
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
—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 first-author · 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.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% | |
| Network and information security
1 paper |
Blockchain and cryptocurrency security · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Transaction processing and concurrency control · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Blockchain and cryptocurrency security › blockchain data management
blockchain database |
0.6 | 1 | 2022 | Hybrid Blockchain Database Systems: Design and Performance · Proc. VLDB Endow. 2022 |
Distributed systems › fault tolerance
byzantine fault tolerance |
0.6 | 1 | 2022 | Hybrid Blockchain Database Systems: Design and Performance · Proc. VLDB Endow. 2022 |
Distributed systems
consensus |
0.6 | 1 | 2022 | Hybrid Blockchain Database Systems: Design and Performance · Proc. VLDB Endow. 2022 |
Distributed systems › fault tolerance › failure models
crash failures |
0.2 | 1 | 2022 | Hybrid Blockchain Database Systems: Design and Performance · Proc. VLDB Endow. 2022 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Hybrid Blockchain Database Systems: Design and PerformanceabstractWith the emergence of hybrid blockchain database systems, we aim to provide an in-depth analysis of the performance and trade-offs among a few representative systems. To achieve this goal, we implement Veritas and BlockchainDB from scratch. For Veritas, we provide two flavors to target the crash fault-tolerant (CFT) and Byzantine fault-tolerant (BFT) application scenarios. Specifically, we implement Veritas with Apache Kafka to target CFT application scenarios, and Veritas with Tendermint to target BFT application scenarios. We compare these three systems with the existing open-source implementation of BigchainDB. BigchainDB uses Tender-mint for consensus and provides two flavors: a default implementation with blockchain pipelining and an optimized version that includes blockchain pipelining and parallel transaction validation. Our experimental analysis confirms that CFT designs, which are typically used by distributed databases, exhibit much higher performance than BFT designs, which are specific to blockchains. On the other hand, our extensive analysis highlights the variety of design choices faced by the developers and sheds some light on the trade-offs that need to be done when designing a hybrid blockchain database system. Zerui Ge, Dumitrel Loghin, Beng Chin Ooi, Pingcheng Ruan, Tianwen Wang |
Proc. VLDB Endow. | 1 |