EDBT 2026 Demo / reviewers in the wild / expert
Mike Hanlon
dblp:63/3139
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2004
—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
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 |
Data stream processing · 44% Transaction processing and concurrency control · 44% Database system architecture and tuning · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Transaction processing and concurrency control
ACID transactions |
0.0 | 1 | 2004 | Publish/Subscribe in NonStop SQL: Transactional Streams in a Relational Context · ICDE 2004 |
Data stream processing › stream processing systems
transactional stream processing |
0.0 | 1 | 2004 | Publish/Subscribe in NonStop SQL: Transactional Streams in a Relational Context · ICDE 2004 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | Publish/Subscribe in NonStop SQL: Transactional Streams in a Relational ContextabstractRelational queries on continuous streams of data are the subject of many recent database research projects. In 1998 a small group of people started a similar project with the goal to transform our product, NonStop SQL/MX, into an active RDBMS. This project tried to integrate functionality of transactional queuing systems with relational tables and with SQL, using simple extensions to the SQL syntax and guaranteeing clearly defined query and transactional semantics. The result is the first commercially available RDBMS that incorporates streams. All data flowing through the system is contained in relational tables and is protected by ACID transactions. Insert and update operations on any NonStop SQL table can be considered publishing of data and can therefore be transparent to the (legacy) applications performing them. Unlike triggers, the publish operation does not increase the path length of the application and it allows the subscriber to execute in a separate transaction. Subscribers, using an extended SQL syntax, see a continuous stream of data, consisting of all rows originally in the table plus all rows that are inserted or updated thereafter. The system scales by using partitioned tables and therefore partitioned streams. Mike Hanlon, Bert Van der Linden, Hansjörg Zeller |
ICDE | 1 |