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Tejasvi Kashi

dblp:396/8639 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Transaction processing and concurrency control › ACID transactions
durability
0.812024
Eventual Durability · Proc. VLDB Endow. 2024
Storage systems › storage reliability › fault-tolerant storage
durability guarantees
0.812024
Eventual Durability · Proc. VLDB Endow. 2024
Distributed systems
fault tolerance
0.812024
Eventual Durability · Proc. VLDB Endow. 2024
Transaction processing and concurrency control › transaction performance
transaction latency
0.212024
Eventual Durability · Proc. VLDB Endow. 2024

Methods — techniques the papers use, named apart from their topics

decoupled commit and durability · 1.5
YearPublicationVenuePosition
2024 Eventual Durability
abstract
For 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