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	<title>Comments on: Parallel Programming in the Age of Big Data</title>
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		<title>By: Big Data = Big Money: EMC Buys Greenplum &#124; Newsroom News</title>
		<link>http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming/#comment-151978</link>
		<dc:creator><![CDATA[Big Data = Big Money: EMC Buys Greenplum &#124; Newsroom News]]></dc:creator>
		<pubDate>Wed, 07 Jul 2010 03:34:56 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=27102#comment-151978</guid>
		<description><![CDATA[&lt;p&gt;[...] company based in Hopkinton, Mass – realizes two simple facts: pure hardware is a commodity and the next industrial revolution is all about data. And that is why it is accelerating its investments in software. Last year it was Data Domain, for [...]&lt;/p&gt;]]></description>
		<content:encoded><![CDATA[<p>[...] company based in Hopkinton, Mass – realizes two simple facts: pure hardware is a commodity and the next industrial revolution is all about data. And that is why it is accelerating its investments in software. Last year it was Data Domain, for [...]</p>
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		<title>By: Big Data Equals Big Money: EMC Buys Greenplum</title>
		<link>http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming/#comment-151977</link>
		<dc:creator><![CDATA[Big Data Equals Big Money: EMC Buys Greenplum]]></dc:creator>
		<pubDate>Wed, 07 Jul 2010 00:45:50 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=27102#comment-151977</guid>
		<description><![CDATA[&lt;p&gt;[...] company based in Hopkinton, Mass – realizes two simple facts: pure hardware is a commodity and the next industrial revolution is all about data. And that is why it is accelerating its investments in software. Last year it was Data Domain, for [...]&lt;/p&gt;]]></description>
		<content:encoded><![CDATA[<p>[...] company based in Hopkinton, Mass – realizes two simple facts: pure hardware is a commodity and the next industrial revolution is all about data. And that is why it is accelerating its investments in software. Last year it was Data Domain, for [...]</p>
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	<item>
		<title>By: woorung</title>
		<link>http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming/#comment-151976</link>
		<dc:creator><![CDATA[woorung]]></dc:creator>
		<pubDate>Thu, 30 Jul 2009 04:42:40 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=27102#comment-151976</guid>
		<description><![CDATA[I think that the final winner between anti-RDBMS and parallel RDBMS will a hybrid system which aims at integrating MapReduce into RDBMS.
Actually, GreenPlum and HadoopDB are doing that.
Both of them are RDBMS advocates since they have lots of knowledge and experience through RDBMS research.
Especially, the hybrid system need SQL-like query analysis &amp; optimization to manipulate distributed DBMSs with MapReduce.
In this point, I think that RDBMS advocates cannot help defeating anti-RDBMS advocates, unfortunately.
Nevertheless, they do not lead IT industry &amp; market due to somewhat high cost.
To reduce cost, most of people want to take advantage of open sources.
Currently, I am a creator of open source &quot;coord&quot;(http://www.coordguru.com), which provides C++ MapReduce framework and distributed key-value store.
In the near future, I believe that such a plan will be achieved on coord project.]]></description>
		<content:encoded><![CDATA[<p>I think that the final winner between anti-RDBMS and parallel RDBMS will a hybrid system which aims at integrating MapReduce into RDBMS.<br />
Actually, GreenPlum and HadoopDB are doing that.<br />
Both of them are RDBMS advocates since they have lots of knowledge and experience through RDBMS research.<br />
Especially, the hybrid system need SQL-like query analysis &amp; optimization to manipulate distributed DBMSs with MapReduce.<br />
In this point, I think that RDBMS advocates cannot help defeating anti-RDBMS advocates, unfortunately.<br />
Nevertheless, they do not lead IT industry &amp; market due to somewhat high cost.<br />
To reduce cost, most of people want to take advantage of open sources.<br />
Currently, I am a creator of open source &#8220;coord&#8221;(<a href="http://www.coordguru.com" rel="nofollow">http://www.coordguru.com</a>), which provides C++ MapReduce framework and distributed key-value store.<br />
In the near future, I believe that such a plan will be achieved on coord project.</p>
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	<item>
		<title>By: Cloudera CEO: Hadoop Will Go Beyond Web Apps</title>
		<link>http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming/#comment-151975</link>
		<dc:creator><![CDATA[Cloudera CEO: Hadoop Will Go Beyond Web Apps]]></dc:creator>
		<pubDate>Tue, 02 Jun 2009 00:05:18 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=27102#comment-151975</guid>
		<description><![CDATA[[...] Parallel Programming in the Age of Big Data [...]]]></description>
		<content:encoded><![CDATA[<p>[...] Parallel Programming in the Age of Big Data [...]</p>
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		<title>By: MapReduce vs. SQL: It&#8217;s Not One or the Other</title>
		<link>http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming/#comment-151974</link>
		<dc:creator><![CDATA[MapReduce vs. SQL: It&#8217;s Not One or the Other]]></dc:creator>
		<pubDate>Tue, 14 Apr 2009 22:53:36 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=27102#comment-151974</guid>
		<description><![CDATA[[...] than does cloud golden child MapReduce. But how shocked should we be, really? After all, choosing a parallel data strategy is not an all-or-nothing [...]]]></description>
		<content:encoded><![CDATA[<p>[...] than does cloud golden child MapReduce. But how shocked should we be, really? After all, choosing a parallel data strategy is not an all-or-nothing [...]</p>
]]></content:encoded>
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	<item>
		<title>By: Big (linked?) data</title>
		<link>http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming/#comment-151973</link>
		<dc:creator><![CDATA[Big (linked?) data]]></dc:creator>
		<pubDate>Sun, 08 Feb 2009 17:50:16 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=27102#comment-151973</guid>
		<description><![CDATA[[...] in the larger universe of data that these organizations inhabit. Big Data unleashed by the “Industrial Revolution of Data”, whether from public agencies, non-profit institutes, or forward-thinking private [...]]]></description>
		<content:encoded><![CDATA[<p>[...] in the larger universe of data that these organizations inhabit. Big Data unleashed by the “Industrial Revolution of Data”, whether from public agencies, non-profit institutes, or forward-thinking private [...]</p>
]]></content:encoded>
	</item>
	<item>
		<title>By: Big Money for Big Database Company</title>
		<link>http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming/#comment-151972</link>
		<dc:creator><![CDATA[Big Money for Big Database Company]]></dc:creator>
		<pubDate>Tue, 13 Jan 2009 17:45:46 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=27102#comment-151972</guid>
		<description><![CDATA[[...] Parallel programming in the age of big data. 2. Programming a parallel future. 3. Terracotta doesn&#8217;t wnat to kill your database, just [...]]]></description>
		<content:encoded><![CDATA[<p>[...] Parallel programming in the age of big data. 2. Programming a parallel future. 3. Terracotta doesn&#8217;t wnat to kill your database, just [...]</p>
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	<item>
		<title>By: Is Big Data near a tipping point? : Data Evolution</title>
		<link>http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming/#comment-151971</link>
		<dc:creator><![CDATA[Is Big Data near a tipping point? : Data Evolution]]></dc:creator>
		<pubDate>Fri, 09 Jan 2009 07:01:08 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=27102#comment-151971</guid>
		<description><![CDATA[[...] in the larger universe of data that these organizations inhabit.  Big Data unleashed by the “Industrial Revolution of Data”, whether from public agencies, non-profit institutes, or forward-thinking private [...]]]></description>
		<content:encoded><![CDATA[<p>[...] in the larger universe of data that these organizations inhabit.  Big Data unleashed by the “Industrial Revolution of Data”, whether from public agencies, non-profit institutes, or forward-thinking private [...]</p>
]]></content:encoded>
	</item>
	<item>
		<title>By: Parallel Programming in the Age of Big Data</title>
		<link>http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming/#comment-151970</link>
		<dc:creator><![CDATA[Parallel Programming in the Age of Big Data]]></dc:creator>
		<pubDate>Tue, 25 Nov 2008 12:15:43 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=27102#comment-151970</guid>
		<description><![CDATA[[...] Full Story [...]]]></description>
		<content:encoded><![CDATA[<p>[...] Full Story [...]</p>
]]></content:encoded>
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	<item>
		<title>By: Mapping and reducing MD trajectories with HiMach : business&#124;bytes&#124;genes&#124;molecules</title>
		<link>http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming/#comment-151969</link>
		<dc:creator><![CDATA[Mapping and reducing MD trajectories with HiMach : business&#124;bytes&#124;genes&#124;molecules]]></dc:creator>
		<pubDate>Tue, 25 Nov 2008 04:47:24 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=27102#comment-151969</guid>
		<description><![CDATA[[...] Parallel Programming in the Age of Big Data [...]]]></description>
		<content:encoded><![CDATA[<p>[...] Parallel Programming in the Age of Big Data [...]</p>
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