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
- 2. Zechao Shang
- 3. Aaron J. Elmore
- 4. Sanjay Krishnan
- 5. Michael J. Franklin
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,131 | Sibyl: Forecasting Time-Evolving Query Workloads | 2024 | SIGMOD | 4.5784634e-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 |
|---|---|---|---|---|
| 41 | NiagaraCQ: A Scalable Continuous Query System for Internet Databases | 2000 | SIGMOD | 0.00073964959 |
| 538 | The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing | 2015 | VLDB | 0.00020678804 |
| 3,002 | Supporting Multiple View Maintenance Policies | 1997 | SIGMOD | 7.7399579e-05 |
| 5,130 | One SQL to Rule Them All – an Efficient and Syntactically Idiomatic Approach to Management of Streams and Tables | 2019 | SIGMOD | 5.6755067e-05 |
| 6,988 | CrocodileDB: Efficient Database Execution through Intelligent Deferment | 2020 | CIDR | 4.8718019e-05 |
| 7,407 | Intermittent Query Processing | 2019 | VLDB | 4.7373205e-05 |
| 8,047 | Thrifty Query Execution via Incrementability | 2020 | SIGMOD | 4.5983505e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 718 | Performance Prediction for Concurrent Database Workloads | 2011 | SIGMOD | 0.0001763106 |
| 5,075 | An Incremental Anytime Algorithm for Multi-Objective Query Optimization | 2015 | SIGMOD | 5.7172118e-05 |
| 8,798 | Resource-Adaptive Query Execution with Paged Memory Management | 2025 | CIDR | 4.4489415e-05 |
| 10,726 | Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries | 2025 | VLDB | 4.1945683e-05 |
| 7,852 | Quality-Driven Continuous Query Execution over Out-of-Order Data Streams | 2015 | SIGMOD | 4.6352012e-05 |
| 7,701 | Resource-efficient Shared Query Execution via Exploiting Time Slackness | 2021 | SIGMOD | 4.6741329e-05 |
| 7,407 | Intermittent Query Processing | 2019 | VLDB | 4.7373205e-05 |
| 9,721 | Adaptive Energy-Control for In-Memory Database Systems | 2018 | SIGMOD | 4.2965439e-05 |
| 8,047 | Thrifty Query Execution via Incrementability | 2020 | SIGMOD | 4.5983505e-05 |
| 6,988 | CrocodileDB: Efficient Database Execution through Intelligent Deferment | 2020 | CIDR | 4.8718019e-05 |