Off-the-shelf Data Analytics on Serverless
Summary: Demonstrates how to transparently run off-the-shelf distributed analytics engines on existing commercial serverless platforms (e.g., unmodified Apache Spark and Drill on AWS Lambda) by adding a thin runtime layer. Presents TPC-H results and a roadmap to make serverless a general-purpose analytics substrate. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Michael Wawrzoniak
- 2. Gianluca Moro
- 3. Rodrigo Bruno
- 4. Ana Klimovic
- 5. Gustavo Alonso
Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,973 | End-to-End Declarative Data Analytics: Co-designing Engines, Interfaces, and Cloud Infrastructure | 2026 | CIDR | 4.1945683e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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