Hardware Acceleration in Commercial Databases: A Case Study of Spatial Operations
Summary: GPU-accelerated spatial operations integrated into a commercial DBMS; architecture enables end-to-end integration. Real-world GIS data show speedups, validating hardware-accelerated spatial query processing as production backend. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Nagender Bandi
- 2. Chengyu Sun
- 3. Divyakant Agrawal
- 4. Amr El Abbadi
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 239 | GPUTeraSort: High Performance Graphics Co-processor Sorting for Large Database Management | 2006 | SIGMOD | 0.00031617428 |
| 775 | Relational Joins on Graphics Processors | 2008 | SIGMOD | 0.00016823862 |
| 1,273 | The Yin and Yang of Processing Data Warehousing Queries on GPU Devices | 2013 | VLDB | 0.00012912938 |
| 2,330 | Concurrent Analytical Query Processing with GPUs | 2014 | VLDB | 9.0192228e-05 |
| 2,882 | Database Compression on Graphics Processors | 2010 | VLDB | 7.9661218e-05 |
| 3,103 | High-Throughput Transaction Executions on Graphics Processors | 2011 | VLDB | 7.5586143e-05 |
| 5,125 | The Art of Balance: A RateupDBTM Experience of Building a CPU/GPU Hybrid Database Product | 2021 | VLDB | 5.679423e-05 |
| 5,457 | Fast and Approximate Stream Mining of Quantiles and Frequencies Using Graphics Processors | 2005 | SIGMOD | 5.4970777e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 478 | Multi-Step Processing of Spatial Joins | 1994 | SIGMOD | 0.0002222104 |
| 2,278 | Hardware Acceleration for Spatial Selections and Joins | 2003 | SIGMOD | 9.1218781e-05 |
| 2,703 | A Raster Approximation for the Processing of Spatial Joins | 1998 | VLDB | 8.2722965e-05 |
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