Databricks Lakeguard: Supporting Fine-grained Access Control and Multi-user Capabilities for Apache Spark Workloads
Summary: Unifies FGAC across SQL, Python, Scala, R, and Spark workloads (row-level filters, column masks). Spark Connect separates client from server and container isolation secures multi-user compute for policy enforcement across languages (SQL, Python, Scala, R). (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Martin Grund (Databricks)
- 2. Stefania Leone (Databricks)
- 3. Herman van Hövell (Databricks)
- 4. Sven Wagner-Boysen (Databricks)
- 5. Sebastian Hillig (Databricks)
- 6. Hyukjin Kwon (Databricks)
- 7. David Lewis (Databricks)
- 8. Jakob Mund (Databricks)
- 9. Polo-Francois Poli (Databricks)
- 10. Lionel Montrieux (Databricks)
- 11. Othon Crelier (Databricks)
- 12. Xiao Li (Databricks)
- 13. Reynold Xin (Databricks)
- 14. Matei Zaharia (Databricks)
- 15. Michalis Petropoulos (Databricks)
- 16. Thanos Papathanasiou (Databricks)
BibTeX Citation
@inproceedings{grund_sigmod25,
title = {{Databricks Lakeguard: Supporting Fine-grained Access Control and Multi-user Capabilities for Apache Spark Workloads}},
author = {Grund, Martin and Leone, Stefania and van Hövell, Herman and Wagner-Boysen, Sven and Hillig, Sebastian and Kwon, Hyukjin and Lewis, David and Mund, Jakob and Poli, Polo-Francois and Montrieux, Lionel and Crelier, Othon and Li, Xiao and Xin, Reynold and Zaharia, Matei and Petropoulos, Michalis and Papathanasiou, Thanos},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3724433},
url = {https://dl.acm.org/doi/10.1145/3722212.3724433},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,605 | Unity Catalog: Open and Universal Governance for the Lakehouse and Beyond | 2025 | SIGMOD | 5.4028924e-05 |
| 10,121 | End-to-End Declarative Data Analytics: Co-designing Engines, Interfaces, and Cloud Infrastructure | 2026 | CIDR | 5.093636e-05 |
| 10,536 | Active Data Lakes: Regaining Physical Data Independence Without Losing Interoperability | 2026 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 24 | Spark SQL: Relational Data Processing in Spark | 2015 | SIGMOD | 0.00054865648 |
| 520 | Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores | 2020 | VLDB | 0.00017136828 |
| 1,138 | Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics | 2021 | CIDR | 0.00012023643 |
| 4,649 | BigLake: BigQuery’s Evolution toward a Multi-Cloud Lakehouse | 2024 | SIGMOD | 6.586622e-05 |
| 5,983 | Adaptive and Robust Query Execution for Lakehouses at Scale | 2024 | VLDB | 6.0206841e-05 |
| 6,553 | Containerized Execution of UDFs: An Experimental Evaluation | 2022 | VLDB | 5.8417517e-05 |
| 7,401 | Membrane - Safe and Performant Data Access Controls in Apache Spark in the Presence of Imperative Code | 2024 | VLDB | 5.6255291e-05 |
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| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,824 | Photon: A Fast Query Engine for Lakehouse Systems | 2022 | SIGMOD |
| 2 | 520 | Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores | 2020 | VLDB |
| 3 | 10,536 | Active Data Lakes: Regaining Physical Data Independence Without Losing Interoperability | 2026 | VLDB |
| 4 | 5,983 | Adaptive and Robust Query Execution for Lakehouses at Scale | 2024 | VLDB |
| 5 | 13,301 | Blink Twice - Automatic Workload Pinning and Regression Detection for Versionless Apache Spark using Retries | 2025 | SIGMOD |
| 6 | 3,411 | Scaling Spark in the Real World: Performance and Usability | 2015 | VLDB |
| 7 | 4,649 | BigLake: BigQuery’s Evolution toward a Multi-Cloud Lakehouse | 2024 | SIGMOD |
| 8 | 8,605 | Unity Catalog: Open and Universal Governance for the Lakehouse and Beyond | 2025 | SIGMOD |
| 9 | 7,780 | Petabyte-Scale Row-Level Operations in Data Lakehouses | 2024 | VLDB |
| 10 | 7,401 | Membrane - Safe and Performant Data Access Controls in Apache Spark in the Presence of Imperative Code | 2024 | VLDB |