Amazon Redshift Re-invented
Summary: Survey Redshift’s evolution to a serverless, autonomic cloud data warehouse at petabyte scale. Highlights include tiered storage, multi-cluster auto-scaling, cross-cluster sharing, AQUA, Spectrum, PartiQL, streaming, Redshift ML, and federated queries/materialized views. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Nikos Armenatzoglou
- 2. Sanuj Basu
- 3. Naga Bhanoori
- 4. Mengchu Cai
- 5. Naresh Chainani
- 6. Kiran Chinta
- 7. Venkatraman Govindaraju
- 8. Todd J. Green
- 9. Monish Gupta
- 10. Sebastian Hillig
- 11. Eric Hotinger
- 12. Yan Leshinksy
- 13. Jintian Liang
- 14. Michael McCreedy
- 15. Fabian Nagel
- 16. Ippokratis Pandis
- 17. Panos Parchas
- 18. Rahul Pathak
- 19. Orestis Polychroniou
- 20. Foyzur Rahman
- 21. Gaurav Saxena
- 22. Gokul Soundararajan
- 23. Sriram Subramanian
- 24. Doug Terry
Incoming Citations (Sorted by Pagerank)
Showing 15 of 65 citing papers.
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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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 156 | Amazon Aurora: Design Considerations for High Throughput Cloud-Native Relational Databases | 2017 | SIGMOD | 0.00040504295 |
| 6,972 | Predicate Caching: Query-Driven Secondary Indexing for Cloud Data Warehouses | 2024 | SIGMOD | 4.8785237e-05 |
| 167 | The Snowflake Elastic Data Warehouse | 2016 | SIGMOD | 0.00039180521 |
| 3,178 | Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet | 2024 | VLDB | 7.4325992e-05 |
| 5,832 | Stage: Query Execution Time Prediction in Amazon Redshift | 2024 | SIGMOD | 5.3111109e-05 |
| 7,337 | Unified Spatial Analytics from Heterogeneous Sources with Amazon Redshift | 2020 | SIGMOD | 4.7584825e-05 |
| 5,634 | Intelligent Scaling in Amazon Redshift | 2024 | SIGMOD | 5.4000904e-05 |
| 4,593 | Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift | 2023 | SIGMOD | 6.0606891e-05 |
| 426 | Amazon Redshift and the Case for Simpler Data Warehouses | 2015 | SIGMOD | 0.00023594359 |
| 3,844 | The evolution of Amazon Redshift (extended abstract) | 2021 | VLDB | 6.7076451e-05 |