Azure Data Lake Store: A Hyperscale Distributed File Service for Big Data Analytics
Summary: ADLS is a fully-managed, exabyte-scale file service optimized for parallel big-data analytics, unifying HDFS compatibility with Cosmos semantics and co-located compute/data. It bridges Cosmos and Hadoop with an HDFS-compatible API, adds multi-tier storage and security, and outlines Cosmos-to-ADLS migration. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Raghu Ramakrishnan (Microsoft)
- 2. Baskar Sridharan (Microsoft)
- 3. John R. Douceur (Microsoft)
- 4. Pavan Kasturi (Microsoft)
- 5. Balaji Krishnamachari-Sampath (Microsoft)
- 6. Karthick Krishnamoorthy (Microsoft)
- 7. Peng Li (Microsoft)
- 8. Mitica Manu (Microsoft)
- 9. Spiro Michaylov (Microsoft)
- 10. Rogério Ramos (Microsoft)
- 11. Neil Sharman (Microsoft)
- 12. Zee Xu (Microsoft)
- 13. Youssef Barakat (Microsoft)
- 14. Chris Douglas (Microsoft)
- 15. Richard Draves (Microsoft)
- 16. Shrikant S Naidu (Microsoft)
- 17. Shankar Shastry (Microsoft)
- 18. Atul Sikaria (Microsoft)
- 19. Simon Sun (Microsoft)
- 20. Ramarathnam Venkatesan (Microsoft)
BibTeX Citation
@inproceedings{ramakrishnan_sigmod17,
title = {{Azure Data Lake Store: A Hyperscale Distributed File Service for Big Data Analytics}},
author = {Ramakrishnan, Raghu and Sridharan, Baskar and Douceur, John R. and Kasturi, Pavan and Krishnamachari-Sampath, Balaji and Krishnamoorthy, Karthick and Li, Peng and Manu, Mitica and Michaylov, Spiro and Ramos, Rogério and Sharman, Neil and Xu, Zee and Barakat, Youssef and Douglas, Chris and Draves, Richard and Naidu, Shrikant S and Shastry, Shankar and Sikaria, Atul and Sun, Simon and Venkatesan, Ramarathnam},
series = {{SIGMOD} '17},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3035918.3056100},
url = {https://dl.acm.org/doi/10.1145/3035918.3056100},
year = {2017}
}
Incoming Citations (Sorted by Pagerank)
Showing 23 of 23 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 30 | SCOPE: Easy and Efficient Parallel Processing of Massive Data Sets | 2008 | VLDB | 0.00051174276 |
| 38 | Hekaton: SQL Server’s Memory-Optimized OLTP Engine | 2013 | SIGMOD | 0.00047648573 |
| 144 | Megastore: Providing Scalable, Highly Available Storage for Interactive Services | 2011 | CIDR | 0.00029554682 |
| 1,267 | Using Paxos to Build a Scalable, Consistent, and Highly Available Datastore | 2011 | VLDB | 0.0001140641 |
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