DIAMetrics: Benchmarking Query Engines at Scale
Summary: DIAMetrics: benchmarking for query engines with summarization, anonymization, execution, monitoring, regression detection, and alerting. Modular, driver-based design abstracts system specifics via canonical formats, enabling scalable benchmarking across engines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shaleen Deep
- 2. Anja Gruenheid
- 3. Kruthi Nagaraj
- 4. Hiro Naito
- 5. Jeff Naughton
- 6. Stratis Viglas
Incoming Citations (Sorted by Pagerank)
Showing 12 of 12 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 5,810 | Database Benchmarking for Supporting Real-Time Interactive Querying of Large Data | 2020 | SIGMOD | 5.3178017e-05 |
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