{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:05:36Z","timestamp":1767337536842},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,8,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Nowadays, data is produced in every aspect of our lives, leading to a massive amount of information generated every\nsecond. However, this vast amount is often too large to be stored and for many applications the information contained in\nthese data streams is only useful when it is fresh. Batch processing platforms like Hadoop MapReduce do not fit these\nneeds as they require to collect data on disk and process it repeatedly. Therefore, modern data processing engines combine\nthe scalability of distributed architectures with the one-pass semantics of traditional stream engines. In\nthis paper, we survey the current state of the art in scalable stream processing from a user perspective. We examine and\ndescribe their architecture, execution model, programming interface, and data analysis support as well as discuss the\nchallenges and limitations of their APIs. In this connection, we introduce Piglet, an extended Pig Latin language and code\ngenerator that compiles (extended) Pig Latin code into programs for various data processing platforms. Thereby, we discuss\nthe mapping to\nplatform-specic concepts in order to provide a uniform view.<\/jats:p>","DOI":"10.1515\/itit-2016-0001","type":"journal-article","created":{"date-parts":[[2016,6,27]],"date-time":"2016-06-27T16:14:52Z","timestamp":1467044092000},"page":"195-205","source":"Crossref","is-referenced-by-count":1,"title":["Stream processing platforms for analyzing big dynamic data"],"prefix":"10.1515","volume":"58","author":[{"given":"Stefan","family":"Hagedorn","sequence":"first","affiliation":[{"name":"TU Ilmenau, Databases and Information Systems group, D-98693 Ilmenau, Germany"}]},{"given":"Philipp","family":"G\u00f6tze","sequence":"additional","affiliation":[{"name":"TU Ilmenau, Databases and Information Systems group, D-98693 Ilmenau, Germany"}]},{"given":"Omran","family":"Saleh","sequence":"additional","affiliation":[{"name":"TU Ilmenau, Databases and Information Systems group, D-98693 Ilmenau, Germany"}]},{"given":"Kai-Uwe","family":"Sattler","sequence":"additional","affiliation":[{"name":"TU Ilmenau, Databases and Information Systems group, D-98693 Ilmenau, Germany"}]}],"member":"374","published-online":{"date-parts":[[2016,6,24]]},"container-title":["it - Information Technology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.degruyter.com\/view\/j\/itit.2016.58.issue-4\/itit-2016-0001\/itit-2016-0001.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2016-0001\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2016-0001\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,23]],"date-time":"2021-06-23T11:44:46Z","timestamp":1624448686000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2016-0001\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,6,24]]},"references-count":0,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2016,6,24]]},"published-print":{"date-parts":[[2016,8,28]]}},"alternative-id":["10.1515\/itit-2016-0001"],"URL":"https:\/\/doi.org\/10.1515\/itit-2016-0001","relation":{},"ISSN":["1611-2776","2196-7032"],"issn-type":[{"value":"1611-2776","type":"print"},{"value":"2196-7032","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,6,24]]}}}