Jeffrey Helt

dblp:200/8024 · DBLP profile ↗
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6ranked-venue papers
3as first author
5since 2021 · last 2025
0000-0003-1192-7111ORCID · corroborated

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

Computer networks · 2 · 1 since 2021Databases, data management, data science and information retrieval · 2 · 2 first-author · 2 since 2021Systems, architecture and hardware · 1 · 1 since 2021Software engineering, systems software and programming languages · 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.

Databases, data mining, and information retrieval
4 papers
Transaction processing and concurrency control · 80% Distributed and cloud data management · 15% Query processing and optimization · 6%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 72% Memory systems · 28%
Computer networks
1 paper
Software-defined and programmable networks · 100%

Topics — the 11 heaviest of 13, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Transaction processing and concurrency control
concurrency control
2.132025
C5: cloned concurrency control that always keeps up · VLDB J. 2025
Morty: Scaling Concurrency Control with Re-Execution · EuroSys 2023
C5: Cloned Concurrency Control That Always Keeps Up · Proc. VLDB Endow. 2022
Transaction processing and concurrency control › concurrency control
serializable concurrency control
0.712023
Morty: Scaling Concurrency Control with Re-Execution · EuroSys 2023
Distributed and cloud data management
data replication
0.612022
C5: Cloned Concurrency Control That Always Keeps Up · Proc. VLDB Endow. 2022
Distributed systems
consistency models
0.512021
Regular Sequential Serializability and Regular Sequential Consistency · SOSP 2021
Memory systems › memory consistency › memory consistency model
sequential consistency
0.512021
Regular Sequential Serializability and Regular Sequential Consistency · SOSP 2021
Distributed systems › concurrency control
serializability
0.512021
Regular Sequential Serializability and Regular Sequential Consistency · SOSP 2021
Software-defined and programmable networks
network function
0.412019
Alembic: Automated Model Inference for Stateful Network Functions · NSDI 2019
Transaction processing and concurrency control
high-contention workloads
0.212023
Morty: Scaling Concurrency Control with Re-Execution · EuroSys 2023
Transaction processing and concurrency control › isolation levels
snapshot isolation
0.212022
C5: Cloned Concurrency Control That Always Keeps Up · Proc. VLDB Endow. 2022
Distributed systems
replication
0.112021
Regular Sequential Serializability and Regular Sequential Consistency · SOSP 2021
Distributed systems › consistency models
weak consistency
0.112021
Regular Sequential Serializability and Regular Sequential Consistency · SOSP 2021

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

model inference · 0.8formal specification · 0.5
YearPublicationVenuePosition
2025 C5: cloned concurrency control that always keeps up
Jeffrey Helt, Daniel J. Abadi, Wyatt Lloyd, Jose M. Faleiro
VLDB J.1
2024 Accelerating Skewed Workloads With Performance Multipliers in the TurboDB Distributed Database
Jennifer Lam, Jeffrey Helt, Wyatt Lloyd, Haonan Lu
NSDI2
2023 Morty: Scaling Concurrency Control with Re-Execution
abstract
Serializable systems often perform poorly under high contention. In this work, we analyze this performance limitation through a novel take on conflict windows. Through the lens of these windows, we develop a new concurrency control technique that leverages transaction re-execution to improve throughput scalability under high contention. Our system, Morty, achieves up to 1.7x-96x the throughput of state-of-the-art systems, with similar or better latency.
Matthew Burke 0001, Florian Suri-Payer, Jeffrey Helt, Lorenzo Alvisi, Natacha Crooks
EuroSys3
2022 C5: Cloned Concurrency Control That Always Keeps Up
abstract
Asynchronously replicated primary-backup databases are commonly deployed to improve availability and offload read-only transactions. To both apply replicated writes from the primary and serve read-only transactions, the backups implement a cloned concurrency control protocol. The protocol ensures read-only transactions always return a snapshot of state that previously existed on the primary. This compels the backup to exactly copy the commit order resulting from the primary's concurrency control. Existing cloned concurrency control protocols guarantee this by limiting the backup's parallelism. As a result, the primary's concurrency control executes some workloads with more parallelism than these protocols. In this paper, we prove that this parallelism gap leads to unbounded replication lag, where writes can take arbitrarily long to replicate to the backup and which has led to catastrophic failures in production systems. We then design C5, the first cloned concurrency protocol to provide bounded replication lag. We implement two versions of C5: Our evaluation in MyRocks, a widely deployed database, demonstrates C5 provides bounded replication lag. Our evaluation in Cicada, a recent in-memory database, demonstrates C5 keeps up with even the fastest of primaries.
Jeffrey Helt, Daniel J. Abadi, Wyatt Lloyd, Jose M. Faleiro
Proc. VLDB Endow.1
2021 Regular Sequential Serializability and Regular Sequential Consistency
abstract
Strictly serializable (linearizable) services appear to execute transactions (operations) sequentially, in an order consistent with real time. This restricts a transaction's (operation's) possible return values and in turn, simplifies application programming. In exchange, strictly serializable (linearizable) services perform worse than those with weaker consistency. But switching to such services can break applications.
Jeffrey Helt, Matthew Burke 0001, Amit Levy 0001, Wyatt Lloyd
SOSP1
2019 Alembic: Automated Model Inference for Stateful Network Functions
Soo-Jin Moon, Jeffrey Helt, Yves Bieri, Sujata Banerjee, Vyas Sekar, Wenfei Wu, Mihalis Yannakakis, Ying Zhang 0022
NSDI2