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	<title>GigaOM &#187; Lexis-Nexis</title>
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		<title>GigaOM &#187; Lexis-Nexis</title>
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		<title>Can LexisNexis build a Hadoop-killer?</title>
		<link>http://gigaom.com/2012/03/22/lexis-nexis-structure-data-2012/</link>
		<comments>http://gigaom.com/2012/03/22/lexis-nexis-structure-data-2012/#comments</comments>
		<pubDate>Thu, 22 Mar 2012 15:47:37 +0000</pubDate>
		<dc:creator>Mathew Ingram</dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Armando Escalante]]></category>
		<category><![CDATA[big data]]></category>
		<category><![CDATA[Lexis-Nexis]]></category>
		<category><![CDATA[Structure Data]]></category>
		<category><![CDATA[Structure:Data 2012]]></category>

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		<description><![CDATA[Hadoop may be the current leader of the pack when it comes to handling big data, but LexisNexis says at Structure:Data the system it developed for its own internal data use -- and recently open-sourced -- is a viable alternative and in some cases is superior.<img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gigaom.com&#038;blog=14960843&#038;post=502566&#038;subd=gigaom2&#038;ref=&#038;feed=1" width="1" height="1" />]]></description>
				<content:encoded><![CDATA[<p>LexisNexis is a giant company, part of the Reed Elsevier information empire, but when it comes to handling big data, it is in the unusual position of being the underdog. The leader of the pack is Hadoop, which has already amassed a large and rapidly-growing following for its ability to manage large databases — but Armando Escalante of LexisNexis told attendees at GigaOM’s <a href="http://event.gigaom.com/structuredata/?utm_source=tech&amp;utm_medium=editorial&amp;utm_campaign=intext&amp;utm_term=502566+lexis-nexis-structure-data-2012&amp;utm_content=mathewingram">Structure:Data</a> conference in New York on Thursday that he believes the company has built what <del datetime="2012-03-22T20:24:41+00:00">could be</del> others might call a Hadoop killer. Originally developed to handle LexisNexis’ own internal data needs, the HPCC system was open-sourced nine months ago, and Escalante said it is already outperforming Hadoop in a number of ways.</p>
<div id="attachment_502557" class="wp-caption alignright" style="width: 310px"><a href="http://gigaom.com/2012/03/22/lexis-nexis-structure-data-2012/1z5o2297/" rel="attachment wp-att-502557"><img title="Armando Escalante of LexisNexis at Structure:Data 2012" src="http://gigaom2.files.wordpress.com/2012/03/1z5o2297.jpg?w=300&#038;h=200" alt="Armando Escalante of LexisNexis at Structure:Data 2012" width="300" height="200" class="size-medium wp-image-502557"></a><p class="wp-caption-text">(c) 2012 Pinar Ozger. pinar@pinarozger.com</p></div>
<p>Because LexisNexis has so much data that it needs to analyze and provide to clients for its legal and government services, Escalante said that the company began building its own internal data-handling platform almost a decade ago, before “big data” even became a buzzword. “We already run our business on this, end-to-end,” he said. Once it became obvious that Hadoop was becoming a popular solution, LexisNexis decided to open-source the project and use the knowledge of a community of users and developers to improve and expand it.</p>
<p>Escalante said the LexisNexis’ system offers a number of features that Hadoop doesn’t, including a big-data delivery engine, and that it is building a layer that will allow its system to handle data from Hadoop. In fact, he said in a recent test a single LexisNexis node was 20-percent faster than a multi-node Hadoop configuration. But the biggest advantage that LexisNexis has, according to Escalante, is that because it is a large company and has already been using the system internally for years, the banks and insurance companies that make up a majority of its clients are more likely to want to use it than Hadoop.</p>
<p>“We have most of the banks and insurance companies as clients, and we are doing proof-of-concept tests with many of them now, and I think they may be more comfortable working with a company that’s not a startup,” Escalante said. “Big companies want a neck to squeeze sometimes, and LexisNexis has a big neck.”</p>
<p><a href="http://pro.gigaom.com/do/structuredata2012-livestream-signup?utm_source=tech&amp;utm_medium=editorial&amp;utm_campaign=intext&amp;utm_term=502566+lexis-nexis-structure-data-2012&amp;utm_content=mathewingram">Watch the livestream</a> of Structure:Data here.</p>
<p><strong>Update:</strong> This post was updated to reflect that moderator Derrick Harris described the project as a “Hadoop killer,” not Escalante.</p>
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<br />  <img alt="" border="0" src="http://stats.wordpress.com/b.gif?host=gigaom.com&#038;blog=14960843&#038;post=502566&#038;subd=gigaom2&#038;ref=&#038;feed=1" width="1" height="1" /><p><a href="http://pubads.g.doubleclick.net/gampad/jump?iu=/1008864/GigaOM_RSS_300x250&#038;sz=300x250&#038;c=608189"><img src="http://pubads.g.doubleclick.net/gampad/ad?iu=/1008864/GigaOM_RSS_300x250&#038;sz=300x250&#038;c=608189" /></a></p><p><strong>Related research and analysis from GigaOM Pro:</strong><br />Subscriber content. <a href="http://pro.gigaom.com/?utm_source=tech&utm_medium=editorial&utm_campaign=auto3&utm_term=502566+lexis-nexis-structure-data-2012&utm_content=mathewingram">Sign up for a free trial</a>.</p><ul><li><a href="http://pro.gigaom.com/2012/05/the-importance-of-putting-the-u-and-i-in-visualization/?utm_source=tech&utm_medium=editorial&utm_campaign=auto3&utm_term=502566+lexis-nexis-structure-data-2012&utm_content=mathewingram">The importance of putting the U and I in visualization</a></li><li><a href="http://pro.gigaom.com/2012/03/a-near-term-outlook-for-big-data/?utm_source=tech&utm_medium=editorial&utm_campaign=auto3&utm_term=502566+lexis-nexis-structure-data-2012&utm_content=mathewingram">A near-term outlook for big data</a></li><li><a href="http://pro.gigaom.com/2011/11/dissecting-the-data-5-issues-for-our-digital-future/?utm_source=tech&utm_medium=editorial&utm_campaign=auto3&utm_term=502566+lexis-nexis-structure-data-2012&utm_content=mathewingram">Dissecting the data: 5 issues for our digital future</a></li></ul>]]></content:encoded>
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			<media:title type="html">Armando Escalante of LexisNexis at Structure:Data 2012</media:title>
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			<media:title type="html">Mathew</media:title>
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			<media:title type="html">Armando Escalante of LexisNexis at Structure:Data 2012</media:title>
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