{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T16:50:26Z","timestamp":1791305426106,"version":"4.3.1"},"reference-count":10,"publisher":"Association for Computing Machinery (ACM)","issue":"13","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2014,8]]},"abstract":"<jats:p>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 na\u00efve 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.<\/jats:p>","DOI":"10.14778\/2733004.2733048","type":"journal-article","created":{"date-parts":[[2015,5,12]],"date-time":"2015-05-12T15:37:52Z","timestamp":1431445072000},"page":"1633-1636","source":"Crossref","is-referenced-by-count":61,"title":["S-Store"],"prefix":"10.14778","volume":"7","author":[{"given":"Ugur","family":"Cetintemel","sequence":"first","affiliation":[{"name":"Brown University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiang","family":"Du","sequence":"additional","affiliation":[{"name":"Intel Labs"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tim","family":"Kraska","sequence":"additional","affiliation":[{"name":"Brown University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel","family":"Madden","sequence":"additional","affiliation":[{"name":"MIT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Maier","sequence":"additional","affiliation":[{"name":"Portland State University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Meehan","sequence":"additional","affiliation":[{"name":"Brown University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Pavlo","sequence":"additional","affiliation":[{"name":"CMU"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Stonebraker","sequence":"additional","affiliation":[{"name":"MIT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erik","family":"Sutherland","sequence":"additional","affiliation":[{"name":"Portland State University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nesime","family":"Tatbul","sequence":"additional","affiliation":[{"name":"Intel Labs and MIT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristin","family":"Tufte","sequence":"additional","affiliation":[{"name":"Portland State University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Wang","sequence":"additional","affiliation":[{"name":"MIT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stanley","family":"Zdonik","sequence":"additional","affiliation":[{"name":"Brown University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2014,8]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"CitiBike. http:\/\/www.citibikenyc.com\/.  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How will the database incumbents respond to NoSQL and NewSQL? The 451 Group , 2011 . M. Aslett. How will the database incumbents respond to NoSQL and NewSQL? 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