EDBT 2026 Demo / reviewers in the wild / expert
Darren Pepper
dblp:273/7136
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1
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 |
Database system architecture and tuning · 33% Data stream processing · 33% Query processing and optimization · 33% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 100% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Query processing and optimization
SQL query processing |
0.4 | 1 | 2020 | Db2 Event Store: A Purpose-Built IoT Database Engine · Proc. VLDB Endow. 2020 |
Cloud and datacenter computing
database-as-a-service |
0.1 | 1 | 2020 | Db2 Event Store: A Purpose-Built IoT Database Engine · Proc. VLDB Endow. 2020 |
Methods — techniques the papers use, named apart from their topics
columnar storage · 0.9SQL compiler reuse · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Db2 Event Store: A Purpose-Built IoT Database EngineabstractThe requirements of Internet of Things (IoT) workloads are unique in the database space. While significant effort has been spent over the last decade rearchitecting OLTP and Analytics workloads for the public cloud, little has been done to rearchitect IoT workloads for the cloud. In this paper we present IBM Db2 Event Store ™ , a cloud-native database system designed specifically for IoT workloads, which require extremely high-speed ingest, efficient and open data storage, and near real-time analytics. Additionally, by leveraging the Db2 SQL compiler, optimizer and runtime, developed and refined over the last 30 years, we demonstrate that rearchitecting for the public cloud doesn't require rewriting all components. Reusing components that have been built out and optimized for decades dramatically reduced the development effort and immediately provided rich SQL support and excellent run-time query performance. Christian Garcia-Arellano, Adam J. Storm, David Kalmuk, Hamdi Roumani, Ron Barber, Yuanyuan Tian 0001, Richard Sidle, Fatma Özcan 0001, Matt Spilchen, Josh Tiefenbach, Daniel C. Zilio, Lan Pham, Kostas Rakopoulos, Alexander Cheung, Darren Pepper, Imran Sayyid, Gidon Gershinsky, Gal Lushi, Hamid Pirahesh |
Proc. VLDB Endow. | 15 |