S-Store: Streaming Meets Transaction Processing
Summary: S-Store fuses streaming and OLTP in an H-Store-based in-memory system, introducing stream transactions with ACID and stream-oriented guarantees. It delivers competitive or superior throughput to H-Store, Esper, and Storm while strengthening correctness. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. John Meehan (Brown University)
- 2. Nesime Tatbul (Intel; Massachusetts Institute of Technology)
- 3. Stan Zdonik (Brown University)
- 4. Cansu Aslantas (Brown University)
- 5. Ugur Cetintemel (Brown University)
- 6. Jiang Du (University of Toronto)
- 7. Tim Kraska (Brown University)
- 8. Samuel Madden (Massachusetts Institute of Technology)
- 9. David Maier (Portland State University)
- 10. Andrew Pavlo (Carnegie Mellon University)
- 11. Michael Stonebraker (Massachusetts Institute of Technology)
- 12. Kristin Tufte (Portland State University)
- 13. Hao Wang (Massachusetts Institute of Technology)
BibTeX Citation
@article{meehan_vldb15,
title = {{S-Store: Streaming Meets Transaction Processing}},
author = {Meehan, John and Tatbul, Nesime and Zdonik, Stan and Aslantas, Cansu and Cetintemel, Ugur and Du, Jiang and Kraska, Tim and Madden, Samuel and Maier, David and Pavlo, Andrew and Stonebraker, Michael and Tufte, Kristin and Wang, Hao},
journal = {PVLDB},
series = {{VLDB} '15},
volume = {8},
number = {13},
pages = {2134--2145},
doi = {10.14778/2831360.2831367},
url = {https://doi.org/10.14778/2831360.2831367},
year = {2015}
}Incoming Citations (Sorted by Pagerank)
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