{"id":9013,"date":"2013-09-30T08:40:00","date_gmt":"2013-09-30T08:40:00","guid":{"rendered":"http:\/\/www.cloudcomputing-news.net\/blog-hub\/2013\/sep\/30\/teradata-1410-ups-in-memory-and-in-database-analytics\/"},"modified":"2013-09-30T08:40:00","modified_gmt":"2013-09-30T08:40:00","slug":"teradata-14-10-ups-in-memory-and-in-database-analytics","status":"publish","type":"post","link":"https:\/\/icloud.pe\/blog\/teradata-14-10-ups-in-memory-and-in-database-analytics\/","title":{"rendered":"Teradata 14.10 ups in-memory and in-database analytics"},"content":{"rendered":"<p><strong>Tony Baer, Principal Analyst, Software &ndash; Information Management<\/strong><\/p>\n<p>The recently released Teradata 14.10 platform adds several features that one-up and surpass some of its newer analytic platform rivals. Highlights include dynamic tiering of hot data into memory, increased support for in-database analytics, better connectivity to Hadoop, and new optimizations for R implementation that fully exploit parallel processing. <\/p>\n<p>Some of the enhancements, such as in-memory tiering, in-database analytic functions, and tighter Hadoop integration, are not necessarily unique to Teradata, but the implementations are. As for R scale-up, Teradata is uniquely applying MapReduce-like enhancements to enable R to better utilize the platform&rsquo;s massively parallel architecture. <\/p>\n<p>In sum, the enhancements are essential for maintaining Teradata&rsquo;s premium positioning for scalability and performance for workloads that still require the service levels and data protections offered by the SQL environment.<\/p>\n<h3>Taking advantage of memory<\/h3>\n<p>This is an ongoing theme for all data platforms, both &#8230;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tony Baer, Principal Analyst, Software &ndash; Information Management<br \/>\nThe recently released Teradata 14.10 platform adds several features that one-up and surpass some of its newer analytic platform rivals. Highlights include dynamic tiering of hot data&#8230;<\/p>\n","protected":false},"author":9,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-9013","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/9013","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/comments?post=9013"}],"version-history":[{"count":0,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/9013\/revisions"}],"wp:attachment":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/media?parent=9013"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/categories?post=9013"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/tags?post=9013"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}