Demo Data from VLDB 2026 / reviewers in the wild / expert
Marc Seidemann
dblp:164/3486
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2 · 2 first-author
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 |
Storage systems · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Data stream processing · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems
indexing |
0.4 | 1 | 2019 | ChronicleDB: A High-Performance Event Store · ACM Trans. Database Syst. 2019 |
Storage systems
storage reliability |
0.4 | 1 | 2019 | ChronicleDB: A High-Performance Event Store · ACM Trans. Database Syst. 2019 |
Data stream processing
event monitoring |
0.1 | 1 | 2019 | ChronicleDB: A High-Performance Event Store · ACM Trans. Database Syst. 2019 |
Methods — techniques the papers use, named apart from their topics
experimental evaluation · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | ChronicleDB: A High-Performance Event StoreabstractReactive security monitoring, self-driving cars, the Internet of Things (IoT), and many other novel applications require systems for both writing events arriving at very high and fluctuating rates to persistent storage as well as supporting analytical ad hoc queries. As standard database systems are not capable of delivering the required write performance, log-based systems, key-value stores, and other write-optimized data stores have emerged recently. However, the drawbacks of these systems are a fair query performance and the lack of suitable instant recovery mechanisms in case of system failures. In this article, we present ChronicleDB, a novel database system with a storage layout tailored for high write performance under fluctuating data rates and powerful indexing capabilities to support a variety of queries. In addition, ChronicleDB offers low-cost fault tolerance and instant recovery within milliseconds. Unlike previous work, ChronicleDB is designed either as a serverless library to be tightly integrated in an application or as a standalone database server. Our results of an experimental evaluation with real and synthetic data reveal that ChronicleDB clearly outperforms competing systems with respect to both write and query performance. Marc Seidemann, Nikolaus Glombiewski, Michael Körber, Bernhard Seeger |
ACM Trans. Database Syst. | 1 |
| 2017 | ChronicleDB: A High-Performance Event Store
Marc Seidemann, Bernhard Seeger |
EDBT | 1 |
| 2017 | Behavior Analysis for Safety and Security in Automotive SystemsabstractThe connection of automotive systems with other systems such as road-side units, other vehicles, and various servers in the Internet opens up new ways for attackers to remotely access safety relevant subsystems within connected cars. The security of connected cars and the whole vehicular ecosystem is thus of utmost importance for consumer trust and acceptance of this emerging technology. This paper describes an approach for on-board detection of unanticipated sequences of events in order to identify suspicious activities. The results show that this approach is fast enough for in-vehicle application at runtime. Several behavior models and synchronization strategies are analyzed in order to narrow down suspicious sequences of events to be sent in a privacy respecting way to a global security operations center for further in-depth analysis. Roland Rieke, Marc Seidemann, Elise Kengni Talla, Daniel Zelle, Bernhard Seeger |
PDP | 2 |