Hardware Acceleration for Spatial Databases: Building Next-Generation Query Engines Using Ray Tracing Cores
Summary: Repurposes commodity GPU ray-tracing cores for spatial joins, indexing, and Hausdorff distance by recasting search/refinement as ray–geometry intersections. Traces the path from RT programming and operator redesign to Apache SedonaDB deployment. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Rubao Lee (Ohio State University)
- 2. Liang Geng (Ohio State University)
- 3. Xiaodong Zhang (Ohio State University)
BibTeX Citation
@article{lee_vldb26,
title = {{Hardware Acceleration for Spatial Databases: Building Next-Generation Query Engines Using Ray Tracing Cores}},
author = {Lee, Rubao and Geng, Liang and Zhang, Xiaodong},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4862--4866},
doi = {10.14778/3827998.3828056},
url = {https://doi.org/10.14778/3827998.3828056},
year = {2026}
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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 |
|---|---|---|---|---|
| 3,689 | RTIndex: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing | 2023 | VLDB | 7.0943075e-05 |
| 6,444 | RTScan: Efficient Scan with Ray Tracing Cores | 2024 | VLDB | 5.7825648e-05 |
| 6,670 | Composable Data Management: An Execution Overview | 2024 | VLDB | 5.7141674e-05 |
| 6,940 | The Past, Present and Future of Indexing on Persistent Memory | 2022 | VLDB | 5.63864e-05 |
| 7,523 | Workload Placement on Heterogeneous CPU-GPU Systems | 2024 | VLDB | 5.5025409e-05 |
| 10,906 | RayBooster: A Ray Tracing Engine to Accelerate SedonaDB | 2026 | VLDB | 4.9793485e-05 |
| 10,937 | RayDB: Building Databases with Ray Tracing Cores | 2026 | VLDB | 4.9793485e-05 |
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