On Brewing Fresh Espresso: LinkedIn’s Distributed Data Serving Platform
Summary: Espresso: LinkedIn's scalable, document-oriented store with cross-document transactions, real-time indexing, on-the-fly schema evolution, and timeline-consistent change capture. Innovations include a generic distributed cluster manager, partition-aware change capture, and a high-performance inverted index, with empirical results. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Lin Qiao
- 2. Kapil Surlaker
- 3. Shirshanka Das
- 4. Tom Quiggle
- 5. Bob Schulman
- 6. Bhaskar Ghosh
- 7. Antony Curtis
- 8. Oliver Seeliger
- 9. Zhen Zhang
- 10. Aditya Auradkar
- 11. Chris Beavers
- 12. Gregory Brandt
- 13. Mihir Gandhi
- 14. Kishore Gopalakrishna
- 15. Wai Ip
- 16. Swaroop Jagadish
- 17. Shi Lu
- 18. Alexander Pachev
- 19. Aditya Ramesh
- 20. Abraham Sebastian
- 21. Rupa Shanbhag
- 22. Subbu Subramaniam
- 23. Yun Sun
- 24. Sajid Topiwala
- 25. Cuong Tran
- 26. Jemiah Westerman
- 27. David Zhang
Incoming Citations (Sorted by Pagerank)
Showing 14 of 14 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 53 | PNUTS: Yahoo!'s Hosted Data Serving Platform | 2008 | VLDB | 0.00066144767 |
| 189 | Megastore: Providing Scalable, Highly Available Storage for Interactive Services | 2011 | CIDR | 0.00035925334 |
| 890 | F1 – The Fault-Tolerant Distributed RDBMS Supporting Google's Ad Business | 2012 | SIGMOD | 0.00015570935 |
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| 11,491 | A Client-centric Approach to Transactional Datastores | 2021 | SIGMOD | 4.1945683e-05 |
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