Tupleware: "Big" Data, Big Analytics, Small Clusters
Summary: Targets analytics on small clusters (few–dozen nodes) with compute‑intensive, sub‑petabyte workloads rather than cloud‑scale. Compiles workflows of UDFs using database+compiler techniques into highly optimized distributed programs, reporting up to 1000× speedups. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Andrew Crotty (Brown University)
- 2. Alex Galakatos (Brown University)
- 3. Kayhan Dursun (Brown University)
- 4. Tim Kraska (Brown University)
- 5. Ugur Cetintemel (Brown University)
- 6. Stan Zdonik (Brown University)
BibTeX Citation
@inproceedings{crotty_cidr15,
address = {Amsterdam, Netherlands},
series = {{CIDR} '15},
title = {{Tupleware: "Big" Data, Big Analytics, Small Clusters}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Crotty, Andrew and Galakatos, Alex and Dursun, Kayhan and Kraska, Tim and Cetintemel, Ugur and Zdonik, Stan},
year = {2015}
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