F1 Lightning: HTAP as a Service
Summary: F1 Lightning delivers HTAP over existing, independently owned transactional systems and a federated query engine—not a greenfield redesign. Production experience at Google addresses transparent, low-latency transactions and analytics for legacy and new applications. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiacheng Yang (Google)
- 2. Ian Rae (Google)
- 3. Jun Xu (Google)
- 4. Jeff Shute (Google)
- 5. Zhan Yuan (Google)
- 6. Kelvin Lau (Google)
- 7. Qiang Zeng (Google)
- 8. Xi Zhao (Google)
- 9. Jun Ma (Google)
- 10. Ziyang Chen (Google)
- 11. Yuan Gao (Google)
- 12. Qilin Dong (Google)
- 13. Junxiong Zhou (Google)
- 14. Jeremy Wood (Google)
- 15. Goetz Graefe (Google)
- 16. Jeff Naughton (Google)
- 17. John Cieslewicz (Google)
BibTeX Citation
@article{yang_vldb20,
title = {{F1 Lightning: HTAP as a Service}},
author = {Yang, Jiacheng and Rae, Ian and Xu, Jun and Shute, Jeff and Yuan, Zhan and Lau, Kelvin and Zeng, Qiang and Zhao, Xi and Ma, Jun and Chen, Ziyang and Gao, Yuan and Dong, Qilin and Zhou, Junxiong and Wood, Jeremy and Graefe, Goetz and Naughton, Jeff and Cieslewicz, John},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {12},
pages = {3313--3325},
doi = {10.14778/3415478.3415553},
url = {https://doi.org/10.14778/3415478.3415553},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 26 of 26 citing papers.
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 2,871 | SnappyData: A Unified Cluster for Streaming, Transactions, and Interactive Analytics | 2017 | CIDR |
| 2 | 9,335 | Rethink Query Optimization in HTAP Databases | 2023 | SIGMOD |
| 3 | 5,605 | How Good is My HTAP System? | 2022 | SIGMOD |
| 4 | 3,788 | Evolving Databases for New-Gen Big Data Applications | 2017 | CIDR |
| 5 | 1,327 | Hybrid Transactional/Analytical Processing: A Survey | 2017 | SIGMOD |
| 6 | 6,031 | Near-Data Processing in Database Systems on Native Computational Storage under HTAP Workloads | 2022 | VLDB |
| 7 | 3,783 | HTAP Databases: What is New and What is Next | 2022 | SIGMOD |
| 8 | 617 | F1: A Distributed SQL Database That Scales | 2013 | VLDB |
| 9 | 1,576 | F1 – The Fault-Tolerant Distributed RDBMS Supporting Google's Ad Business | 2012 | SIGMOD |
| 10 | 2,831 | F1 Query: Declarative Querying at Scale | 2018 | VLDB |