CrocodileDB in Action: Resource-Efficient Query Execution by Exploiting Time Slackness
Summary: CrocodileDB leverages user-defined time slackness to reduce resource use in stream queries, balancing latency against CPU/memory under a performance goal. InQP defers non-incremental work to cut waste, enabling CPU-latency trade-offs and measurable savings. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Dixin Tang (University of Chicago)
- 2. Zechao Shang (University of Chicago)
- 3. Aaron J. Elmore (University of Chicago)
- 4. Sanjay Krishnan (University of Chicago)
- 5. Michael J. Franklin (University of Chicago)
BibTeX Citation
@article{tang_vldb20,
title = {{CrocodileDB in Action: Resource-Efficient Query Execution by Exploiting Time Slackness}},
author = {Tang, Dixin and Shang, Zechao and Elmore, Aaron J. and Krishnan, Sanjay and Franklin, Michael J.},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {12},
pages = {2937--2940},
doi = {10.14778/3415478.3415513},
url = {https://doi.org/10.14778/3415478.3415513},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,580 | Sibyl: Forecasting Time-Evolving Query Workloads | 2024 | SIGMOD | 5.5925285e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 25 | NiagaraCQ: A Scalable Continuous Query System for Internet Databases | 2000 | SIGMOD | 0.00054667018 |
| 361 | The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing | 2015 | VLDB | 0.00020138717 |
| 2,771 | Supporting Multiple View Maintenance Policies | 1997 | SIGMOD | 8.1455861e-05 |
| 4,907 | One SQL to Rule Them All – an Efficient and Syntactically Idiomatic Approach to Management of Streams and Tables | 2019 | SIGMOD | 6.4494002e-05 |
| 6,684 | CrocodileDB: Efficient Database Execution through Intelligent Deferment | 2020 | CIDR | 5.8036476e-05 |
| 7,200 | Intermittent Query Processing | 2019 | VLDB | 5.6756294e-05 |
| 7,967 | Thrifty Query Execution via Incrementability | 2020 | SIGMOD | 5.5169373e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 624 | Performance Prediction for Concurrent Database Workloads | 2011 | SIGMOD |
| 2 | 4,880 | An Incremental Anytime Algorithm for Multi-Objective Query Optimization | 2015 | SIGMOD |
| 3 | 8,818 | Resource-Adaptive Query Execution with Paged Memory Management | 2025 | CIDR |
| 4 | 10,969 | Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries | 2025 | VLDB |
| 5 | 7,626 | Quality-Driven Continuous Query Execution over Out-of-Order Data Streams | 2015 | SIGMOD |
| 6 | 7,579 | Resource-efficient Shared Query Execution via Exploiting Time Slackness | 2021 | SIGMOD |
| 7 | 7,200 | Intermittent Query Processing | 2019 | VLDB |
| 8 | 9,858 | Adaptive Energy-Control for In-Memory Database Systems | 2018 | SIGMOD |
| 9 | 7,967 | Thrifty Query Execution via Incrementability | 2020 | SIGMOD |
| 10 | 6,684 | CrocodileDB: Efficient Database Execution through Intelligent Deferment | 2020 | CIDR |