Napa: Powering Scalable Data Warehousing with Robust Query Performance at Google
Summary: Napa is Google's analytical data-management backend delivering scalable, sub-second query performance across planet-scale ingests. It achieves robust, availability-aware query processing through aggressive cross-data-center maintenance of materialized views, with configurable freshness, consistency guarantees, and cost/latency tradeoffs for diverse clients. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ankur Agiwal
- 2. Kevin Lai
- 3. Gokul Nath Babu Manoharan
- 4. Indrajit Roy
- 5. Jagan Sankaranarayanan
- 6. Hao Zhang
- 7. Tao Zou
- 8. Min Chen
- 9. Zongchang (Jim) Chen
- 10. Ming Dai
- 11. Thanh Do
- 12. Haoyu Gao
- 13. Haoyan Geng
- 14. Raman Grover
- 15. Bo Huang
- 16. Yanlai Huang
- 17. Zhi (Adam) Li
- 18. Jianyi Liang
- 19. Tao Lin
- 20. Li Liu
- 21. Yao Liu
- 22. Xi Mao
- 23. Yalan (Maya) Meng
- 24. Prashant Mishra
- 25. Jay Patel
- 26. Rajesh S. R.
- 27. Vijayshankar Raman
- 28. Sourashis Roy
- 29. Mayank Singh Shishodia
- 30. Tianhang Sun
- 31. Ye (Justin) Tang
- 32. Junichi Tatemura
- 33. Sagar Trehan
- 34. Ramkumar Vadali
- 35. Prasanna Venkatasubramanian
- 36. Gensheng Zhang
- 37. Kefei Zhang
- 38. Yupu Zhang
- 39. Zeleng Zhuang
- 40. Goetz Graefe
- 41. Divyakant Agrawal
- 42. Jeff Naughton
- 43. Sujata Kosalge
- 44. Hakan Hacigumus
Incoming Citations (Sorted by Pagerank)
Showing 14 of 14 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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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,264 | Online Expansion of Large-scale Data Warehouses | 2011 | VLDB | 4.7842311e-05 |
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| 7,688 | Near-Data Processing in Database Systems on Native Computational Storage under HTAP Workloads | 2022 | VLDB | 4.6772837e-05 |
| 4,530 | Big Metadata: When Metadata is Big Data | 2021 | VLDB | 6.1075429e-05 |
| 3,355 | F1 Query: Declarative Querying at Scale | 2018 | VLDB | 7.1829142e-05 |
| 4,767 | Pinot: Realtime OLAP for 530 Million Users | 2018 | SIGMOD | 5.9364731e-05 |
| 2,844 | Towards Scalable Real-time Analytics: An Architecture for Scale-out of OLxP Workloads | 2015 | VLDB | 8.0243849e-05 |
| 7,953 | Shasta: Interactive Reporting At Scale | 2016 | SIGMOD | 4.613363e-05 |
| 1,814 | Mesa: Geo-Replicated, Near Real-Time, Scalable Data Warehousing | 2014 | VLDB | 0.00010458107 |
| 9,905 | Progressive Partitioning for Parallelized Query Execution in Google's Napa | 2023 | VLDB | 4.258022e-05 |