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Liam Arzola

dblp:357/5558 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0006-1098-4906ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 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 · 100%
Databases, data mining, and information retrieval
1 paper
Query processing and optimization · 50% Transaction processing and concurrency control · 50%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed systems › fault tolerance
byzantine fault tolerance
0.912025
Pesto: Cooking up High Performance BFT Queries · SOSP 2025
Transaction processing and concurrency control › serializability
serializable transactions
0.312025
Pesto: Cooking up High Performance BFT Queries · SOSP 2025
Query processing and optimization
SQL query processing
0.312025
Pesto: Cooking up High Performance BFT Queries · SOSP 2025

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

on-demand synchronization · 1.7leaderless design · 1.7
YearPublicationVenuePosition
2025 Pesto: Cooking up High Performance BFT Queries
abstract
This paper presents Pesto, a high-performance Byzantine Fault Tolerant (BFT) database that offers full SQL compatibility. Pesto intentionally forgoes the use of State Machine Replication (SMR); SMR-based designs offer poor performance due to the several round trips required to order transactions. Pesto, instead, allows for replicas to remain inconsistent, and only synchronizes on demand to ensure that the database remain serializable in the presence of concurrent transactions and malicious actors. On TPC-C, Pesto matches the throughput of Peloton [20] and Postgres [21], two unreplicated SQL database systems, while increasing throughput by 2.3x compared to classic SMR-based BFT-architectures, and reducing latency by 2.7x to 3.9x. Pesto's leaderless design minimizes the impact of replica failures and ensures robust performance.
Florian Suri-Payer, Neil Giridharan, Liam Arzola, Shir Cohen, Lorenzo Alvisi, Natacha Crooks
SOSP3