The Myria Big Data Management and Analytics System and Cloud Service
Summary: End-to-end big-data management and analytics stack and cloud service (Myria) from UW, integrating a scalable parallel engine with domain-scientist-oriented usability and operational tooling. Paper presents Myria's core design choices, innovations, and deployment lessons across real data-science workloads. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jingjing Wang (University of Washington)
- 2. Tobin Baker (University of Washington)
- 3. Magdalena Balazinska (University of Washington)
- 4. Daniel Halperin (Google; University of Washington)
- 5. Brandon Haynes (University of Washington)
- 6. Bill Howe (University of Washington)
- 7. Dylan Hutchison (University of Washington)
- 8. Shrainik Jain (University of Washington)
- 9. Ryan Maas (University of Washington)
- 10. Parmita Mehta (University of Washington)
- 11. Dominik Moritz (University of Washington)
- 12. Brandon Myers (University of Iowa; University of Washington)
- 13. Jennifer Ortiz (University of Washington)
- 14. Dan Suciu (University of Washington)
- 15. Andrew Whitaker (Amazon; University of Washington)
- 16. Shengliang Xu (Pure Storage; University of Washington)
BibTeX Citation
@inproceedings{wang_cidr17,
address = {Amsterdam, Netherlands},
series = {{CIDR} '17},
title = {{The Myria Big Data Management and Analytics System and Cloud Service}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Wang, Jingjing and Baker, Tobin and Balazinska, Magdalena and Halperin, Daniel and Haynes, Brandon and Howe, Bill and Hutchison, Dylan and Jain, Shrainik and Maas, Ryan and Mehta, Parmita and Moritz, Dominik and Myers, Brandon and Ortiz, Jennifer and Suciu, Dan and Whitaker, Andrew and Xu, Shengliang},
year = {2017}
}
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