EDBT 2026 Demo / reviewers in the wild / expert
Kitaek Lee
dblp:333/5590
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · unresolved
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 · 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.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Storage systems · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Query processing and optimization · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems
computational storage |
0.7 | 1 | 2023 | Deploying Computational Storage for HTAP DBMSs Takes More Than Just Computation Offloading · Proc. VLDB Endow. 2023 |
Storage systems › computational storage
in-storage computing |
0.7 | 1 | 2023 | Deploying Computational Storage for HTAP DBMSs Takes More Than Just Computation Offloading · Proc. VLDB Endow. 2023 |
Storage systems › computational storage
computational storage device |
0.2 | 1 | 2023 | Deploying Computational Storage for HTAP DBMSs Takes More Than Just Computation Offloading · Proc. VLDB Endow. 2023 |
Methods — techniques the papers use, named apart from their topics
index prescreening · 1.3canonical representation · 1.3FPGA · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Deploying Computational Storage for HTAP DBMSs Takes More Than Just Computation OffloadingabstractHybrid transactional/analytical processing (HTAP) would overload database systems. To alleviate performance interference between transactions and analytics, recent research pursues the potential of in-storage processing (ISP) using commodity computational storage devices (CSDs). However, in-storage query processing faces technical challenges in HTAP environments. Continuously updated data versions pose two hurdles: (1) data items keep changing, and (2) finding visible data versions incurs excessive data access in CSDs. Such access patterns dominate the cost of query processing, which may hinder the active deployment of CSDs. This paper addresses the core issues by proposing an a nalyt i c offloa d e ngine (AIDE) that transforms engine-specific query execution logic into vendor-neutral computation through a canonical interface. At the core of AIDE are the canonical representation of vendor-specific data and the separate management of data locators. It enables any CSD to execute vendor-neutral operations on canonical tuples with separate indexes, regardless of host databases. To eliminate excessive data access, we prescreen the indexes before offloading; thus, host-side prescreening can obviate the need for running costly version searching in CSDs and boost analytics. We implemented our prototype for PostgreSQL and MyRocks, demonstrating that AIDE supports efficient ISP for two databases using the same FPGA logic. Evaluation results show that AIDE improves query latency up to 42× on PostgreSQL and 34× on MyRocks. Kitaek Lee, Insoon Jo, Jaechan Ahn, Hyuk Lee, Hwang Lee, Woong Sul, Hyungsoo Jung 0001 |
Proc. VLDB Endow. | 1 |