SMOKE: Fine-grained Lineage at Interactive Speed
Summary: SMOKE is an in-memory DB engine that tightly integrates lineage capture into physical operators to minimize overhead and accelerate lineage queries. It uses compact lineage representations and upfront-query-aware optimizations to deliver interactive latency (sub-150 ms) and multi-order-of-magnitude improvements over prior systems on real workloads. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Fotis Psallidas
- 2. Eugene Wu
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,049 | Thrifty Query Execution via Incrementability | 2020 | SIGMOD | 4.5939412e-05 |
| 9,466 | Memory Efficient Scheduling of Query Pipeline Execution | 2022 | CIDR | 4.3314303e-05 |
| 8,725 | OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs | 2023 | VLDB | 4.453957e-05 |
| 7,556 | Interactive Query Explanations Using Fine Grained Provenance | 2022 | SIGMOD | 4.7072603e-05 |
| 10,429 | Unified Lineage System: Tracking Data Provenance at Scale | 2025 | SIGMOD | 4.1905499e-05 |
| 7,754 | Lineage Processing over Correlated Probabilistic Databases | 2010 | SIGMOD | 4.6556861e-05 |
| 5,854 | Tracing Lineage Beyond Relational Operators | 2007 | VLDB | 5.2982313e-05 |
| 11,355 | Lineage Resource Manager | 2022 | SIGMOD | 4.1905499e-05 |
| 1,763 | Efficient Lineage Tracking For Scientific Workflows | 2008 | SIGMOD | 0.00010626896 |
| 11,716 | Demonstration of Smoke: A Deep Breath of Data-Intensive Lineage Applications | 2018 | SIGMOD | 4.1905499e-05 |