Demo Data from EDBT 2026 / reviewers in the wild / expert
Robert Binna
dblp:74/10151
· DBLP profile ↗
2ranked-venue papers
2as first author
1since 2021 · last 2022
0000-0003-1062-8419ORCID · corroborated
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 · 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.
| Databases, data mining, and information retrieval
2 papers |
Indexing and storage engines · 96% Query processing and optimization · 4% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Indexing and storage engines
in-memory index |
0.9 | 2 | 2022 | Height Optimized Tries · ACM Trans. Database Syst. 2022 HOT: A Height Optimized Trie Index for Main-Memory Database Systems · SIGMOD Conference 2018 |
Indexing and storage engines › string indexing
trie index |
0.9 | 2 | 2022 | Height Optimized Tries · ACM Trans. Database Syst. 2022 HOT: A Height Optimized Trie Index for Main-Memory Database Systems · SIGMOD Conference 2018 |
Indexing and storage engines › in-memory index
cache-efficient index |
0.6 | 1 | 2022 | Height Optimized Tries · ACM Trans. Database Syst. 2022 |
Methods — techniques the papers use, named apart from their topics
SIMD · 0.9lightweight compression · 0.6cache-conscious layout · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Height Optimized TriesabstractWe present the Height Optimized Trie (HOT), a fast and space-efficient in-memory index structure. The core algorithmic idea of HOT is to dynamically vary the number of bits considered at each node, which enables a consistently high fanout and thereby good cache efficiency. For a fixed maximum node fanout, the overall tree height is minimal and its structure is deterministically defined. Multiple carefully engineered node implementations using SIMD instructions or lightweight compression schemes provide compactness and fast search and optimize HOT structures for different usage scenarios. Our experiments, which use a wide variety of workloads and data sets, show that HOT outperforms other state-of-the-art index structures for string keys both in terms of search performance and memory footprint, while being competitive for integer keys. Robert Binna, Eva Zangerle, Martin Pichl, Günther Specht, Viktor Leis |
ACM Trans. Database Syst. | 1 |
| 2018 | HOT: A Height Optimized Trie Index for Main-Memory Database SystemsabstractWe present the Height Optimized Trie (HOT), a fast and space-efficient in-memory index structure. The core algorithmic idea of HOT is to dynamically vary the number of bits considered at each node, which enables a consistently high fanout and thereby good cache efficiency. The layout of each node is carefully engineered for compactness and fast search using SIMD instructions. Our experimental results, which use a wide variety of workloads and data sets, show that HOT outperforms other state-of-the-art index structures for string keys both in terms of search performance and memory footprint, while being competitive for integer keys. We believe that these properties make HOT highly useful as a general-purpose index structure for main-memory databases. Robert Binna, Eva Zangerle, Martin Pichl, Günther Specht, Viktor Leis |
SIGMOD Conference | 1 |