Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet
Summary: Telemetry from 400 Amazon Redshift instances shows cloud data-warehouse workloads diverge from TPC-H/DS: prominent write-heavy pipelines, temporal variability in load and query types, repetitive queries, and heavy-tailed distributions of query/workload properties. Argues benchmarks must broaden beyond pure query-engine throughput to model ingestion, temporal dynamics, repetition and tail behavior, and releases a 3-month query-statistics dataset to seed more realistic benchmark design. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Alexander van Renen (University of Technology Nuremberg)
- 2. Dominik Horn (Amazon)
- 3. Pascal Pfeil (Amazon)
- 4. Kapil Vaidya (Amazon)
- 5. Wenjian Dong (Amazon)
- 6. Murali Narayanaswamy (Amazon)
- 7. Zhengchun Liu (Amazon)
- 8. Gaurav Saxena (Amazon)
- 9. Andreas Kipf (University of Technology Nuremberg)
- 10. Tim Kraska (Amazon)
BibTeX Citation
@article{renen_vldb24,
title = {{Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet}},
author = {van Renen, Alexander and Horn, Dominik and Pfeil, Pascal and Vaidya, Kapil and Dong, Wenjian and Narayanaswamy, Murali and Liu, Zhengchun and Saxena, Gaurav and Kipf, Andreas and Kraska, Tim},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {11},
pages = {3694--3706},
doi = {10.14778/3681954.3682031},
url = {https://doi.org/10.14778/3681954.3682031},
year = {2024}
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