dc.contributor.author | Cetintemel, Ugur | |
dc.contributor.author | Tufte, Kristin | |
dc.contributor.author | Wang, Hao | |
dc.contributor.author | Zdonik, Stanley | |
dc.contributor.author | Du, Jiang | |
dc.contributor.author | Kraska, Tim | |
dc.contributor.author | Maier, David | |
dc.contributor.author | Meehan, John | |
dc.contributor.author | Pavlo, Andrew | |
dc.contributor.author | Stonebraker, Michael | |
dc.contributor.author | Sutherland, Erik | |
dc.contributor.author | Madden, Samuel R. | |
dc.contributor.author | Tatbul Bitim, Emine Nesime | |
dc.date.accessioned | 2016-01-19T01:48:04Z | |
dc.date.available | 2016-01-19T01:48:04Z | |
dc.date.issued | 2014-08 | |
dc.identifier.issn | 21508097 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/100909 | |
dc.description.abstract | First-generation streaming systems did not pay much attention to state management via ACID transactions (e.g., [3, 4]). S-Store is a data management system that combines OLTP transactions with stream processing. To create S-Store, we begin with H-Store, a main-memory transaction processing engine, and add primitives to support streaming. This includes triggers and transaction workflows to implement push-based processing, windows to provide a way to bound the computation, and tables with hidden state to implement scoping for proper isolation. This demo explores the benefits of this approach by showing how a naïve implementation of our benchmarks using only H-Store can yield incorrect results. We also show that by exploiting push-based semantics and our implementation of triggers, we can achieve significant improvement in transaction throughput. We demo two modern applications: (i) leaderboard maintenance for a version of "American Idol", and (ii) a city-scale bicycle rental scenario. | en_US |
dc.language.iso | en_US | |
dc.publisher | Association for Computing Machinery (ACM) | en_US |
dc.relation.isversionof | http://dx.doi.org/10.14778/2733004.2733048 | en_US |
dc.rights | Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/ | en_US |
dc.source | MIT web domain | en_US |
dc.title | S-Store: a streaming NewSQL system for big velocity applications | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Ugur Cetintemel, Jiang Du, Tim Kraska, Samuel Madden, David Maier, John Meehan, Andrew Pavlo, Michael Stonebraker, Erik Sutherland, Nesime Tatbul, Kristin Tufte, Hao Wang, and Stanley Zdonik. 2014. S-Store: a streaming NewSQL system for big velocity applications. Proc. VLDB Endow. 7, 13 (August 2014), 1633-1636. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
dc.contributor.mitauthor | Madden, Samuel R. | en_US |
dc.contributor.mitauthor | Stonebraker, Michael | en_US |
dc.contributor.mitauthor | Tatbul Bitim, Emine Nesime | en_US |
dc.contributor.mitauthor | Wang, Hao | en_US |
dc.relation.journal | Proceedings of the VLDB Endowment | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dspace.orderedauthors | Cetintemel, Ugur; Tatbul, Nesime; Tufte, Kristin; Wang, Hao; Zdonik, Stanley; Du, Jiang; Kraska, Tim; Madden, Samuel; Maier, David; Meehan, John; Pavlo, Andrew; Stonebraker, Michael; Sutherland, Erik | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-9184-9058 | |
dc.identifier.orcid | https://orcid.org/0000-0002-7470-3265 | |
mit.license | PUBLISHER_CC | en_US |