EDBT 2026 Demo / reviewers in the wild / expert
Jeremy Meyer
dblp:86/8165
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2010
—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% Query processing and optimization · 33% Transaction processing and concurrency control · 33% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Database system architecture and tuning
main-memory database |
0.1 | 1 | 2010 | Crescando · SIGMOD Conference 2010 |
Query processing and optimization › query execution
scan processing |
0.1 | 1 | 2010 | Crescando · SIGMOD Conference 2010 |
Methods — techniques the papers use, named apart from their topics
parallel query processing · 0.1full-table scan · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | CrescandoabstractThis demonstration presents Crescando, an implementation of a distributed relational table that guarantees predictable response time on unpredictable workloads. In Crescando, data is stored in main memory and accessed via full-table scans. By using scans instead of index lookups, Crescando overcomes the read-write contention in index structures and eliminates the scalability issues that exist in traditional index-based systems. Crescando is specifically designed to process a large number of queries in parallel, allowing high query rates. The goal of this demonstration is to show the ability of Crescando to a) quickly answer arbitrary user-generated queries, and b) execute a large number of queries and updates in parallel, while providing strict response time and data freshness guarantees. Georgios Giannikis, Philipp Unterbrunner, Jeremy Meyer, Gustavo Alonso, Dietmar Fauser, Donald Kossmann |
SIGMOD Conference | 3 |