Demo Data from EDBT 2026 / reviewers in the wild / expert
Tejasvi Kashi
dblp:396/8639
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2024
—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 · 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 |
Distributed systems · 50% Storage systems · 50% | |
| Databases, data mining, and information retrieval
1 paper |
Transaction processing and concurrency control · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Transaction processing and concurrency control › ACID transactions
durability |
0.8 | 1 | 2024 | Eventual Durability · Proc. VLDB Endow. 2024 |
Storage systems › storage reliability › fault-tolerant storage
durability guarantees |
0.8 | 1 | 2024 | Eventual Durability · Proc. VLDB Endow. 2024 |
Distributed systems
fault tolerance |
0.8 | 1 | 2024 | Eventual Durability · Proc. VLDB Endow. 2024 |
Transaction processing and concurrency control › transaction performance
transaction latency |
0.2 | 1 | 2024 | Eventual Durability · Proc. VLDB Endow. 2024 |
Methods — techniques the papers use, named apart from their topics
decoupled commit and durability · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Eventual DurabilityabstractFor latency-critical transactional applications, durability is often what limits performance. That is, executing transactions is fast, but guaranteeing that they are durable is slow. As a result, most of each transaction's latency is attributable to durability. To address this problem, some database systems allow applications to sacrifice durability guarantees in exchange for lower transaction latencies. These ad hoc techniques are effective, but they can make it difficult for applications to understand and manage the risks associated with failures. In this paper, our goal is to offer a more principled foundation for these kinds of performance/durability tradeoffs. The major obstacle to doing this is the transaction model itself, because it couples transaction durability with transaction commit. That is, the model defines a single point at which a transaction becomes visible and durable. This forces all transaction guarantees to wait for the slowest one, which is often durability. The primary contribution of this work is a new eventually durable transaction model, which decouples commit from durability. Transactions commit first, and become durable later. We argue for making this model the basis of the contract between transactional data systems and applications. We describe what it means to correctly implement eventually durable transactions, and consider how they can be exposed to applications. We also describe a prototype implementation of eventual durability in PostgreSQL, and show that it enables applications to reduce transaction latencies while managing the durability risks. Tejasvi Kashi, Kenneth Salem, Jaemyung Kim, Khuzaima Daudjee |
Proc. VLDB Endow. | 1 |