{"id":170875,"date":"2011-11-21T13:31:30","date_gmt":"2011-11-21T13:31:30","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/project\/streams\/"},"modified":"2017-06-19T10:26:41","modified_gmt":"2017-06-19T17:26:41","slug":"streams","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/streams\/","title":{"rendered":"Streams"},"content":{"rendered":"<div class=\"asset-content\">In the streams research project, we propose novel architectures, efficient processing techniques, models, and applications to support time-oriented queries over real-time and offline data streams. Our current focus in the project centers around Trill, a high-performance streaming analytics engine that is now used across Microsoft. Our currect focus areas include efficient query processing, scale-out, resiliency, streaming state management, and unstructured data support.<\/div>\n<p><!-- .asset-content --><\/p>\n<span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span>","protected":false},"excerpt":{"rendered":"<p>In the streams research project, we propose novel architectures, efficient processing techniques, models, and applications to support time-oriented queries over real-time and offline data streams. Our current focus in the project centers around Trill, a high-performance streaming analytics engine that is now used across Microsoft. Our currect focus areas include efficient query processing, scale-out, resiliency, [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"research-area":[13555,13547],"msr-impact-theme":[],"msr-pillar":[],"msr_project_start":"2011-11-21","related-publications":[159592,161408,166281,159593,161550,167653,160094,161984,244505,160249,161985,245552,160417,161997,266391,160425,162047,319952,160426,163577,345572,160917,164964,153171,160918,165116,157952,160919,165416,157953,161365,165420],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"user_nicename","value":"badrishc","display_name":"Badrish Chandramouli","author_link":"<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/people\/badrishc\/\" aria-label=\"Visit the profile page for Badrish Chandramouli\">Badrish Chandramouli<\/a>","is_active":false,"user_id":31166,"last_first":"Chandramouli, Badrish","people_section":0,"alias":"badrishc"}],"msr_research_lab":[199565],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170875"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":2,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170875\/revisions"}],"predecessor-version":[{"id":391496,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170875\/revisions\/391496"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=170875"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=170875"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=170875"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=170875"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}