EDBT 2026 Demo / reviewers in the wild / expert
Jeffrey Helt
dblp:200/8024
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Transaction processing and concurrency control
concurrency control |
2.1 | 3 | 2025 | 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 |
0.7 | 1 | 2023 | Morty: Scaling Concurrency Control with Re-Execution · EuroSys 2023 |
Distributed and cloud data management
data replication |
0.6 | 1 | 2022 | C5: Cloned Concurrency Control That Always Keeps Up · Proc. VLDB Endow. 2022 |
Distributed systems
consistency models |
0.5 | 1 | 2021 | Regular Sequential Serializability and Regular Sequential Consistency · SOSP 2021 |
Memory systems › memory consistency › memory consistency model
sequential consistency |
0.5 | 1 | 2021 | Regular Sequential Serializability and Regular Sequential Consistency · SOSP 2021 |
Distributed systems › concurrency control
serializability |
0.5 | 1 | 2021 | Regular Sequential Serializability and Regular Sequential Consistency · SOSP 2021 |
Software-defined and programmable networks
network function |
0.4 | 1 | 2019 | Alembic: Automated Model Inference for Stateful Network Functions · NSDI 2019 |
Transaction processing and concurrency control
high-contention workloads |
0.2 | 1 | 2023 | Morty: Scaling Concurrency Control with Re-Execution · EuroSys 2023 |
Transaction processing and concurrency control › isolation levels
snapshot isolation |
0.2 | 1 | 2022 | C5: Cloned Concurrency Control That Always Keeps Up · Proc. VLDB Endow. 2022 |
Distributed systems
replication |
0.1 | 1 | 2021 | Regular Sequential Serializability and Regular Sequential Consistency · SOSP 2021 |
Distributed systems › consistency models
weak consistency |
0.1 | 1 | 2021 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 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 |
NSDI | 2 |
| 2023 | Morty: Scaling Concurrency Control with Re-ExecutionabstractSerializable 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 |
EuroSys | 3 |
| 2022 | C5: Cloned Concurrency Control That Always Keeps UpabstractAsynchronously 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 ConsistencyabstractStrictly 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 |
SOSP | 1 |
| 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 |
NSDI | 2 |