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	<title>Gigaom Search &#187; Apache Spark</title>
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		<title>For now, Spark looks like the future of big data</title>
		<link>http://gigaom.com/2015/02/20/for-now-spark-looks-like-the-future-of-big-data/</link>
		<comments>http://gigaom.com/2015/02/20/for-now-spark-looks-like-the-future-of-big-data/#comments</comments>
		<pubDate>Fri, 20 Feb 2015 21:05:38 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[data science]]></category>
		<category><![CDATA[Databricks]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[Structure Data 2015]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=916170</guid>
		<description><![CDATA[Titles can be misleading. For example, the O'Reilly Strata + Hadoop World conference took place in San Jose, California, this week but Hadoop wasn't the star of the show. Based on&#8230;]]></description>
		<wfw:commentRss>http://gigaom.com/2015/02/20/for-now-spark-looks-like-the-future-of-big-data/feed/</wfw:commentRss>
		<slash:comments>5</slash:comments>
		</item>
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		<title>Survey reveals a few interesting numbers about Apache Spark</title>
		<link>https://gigaom.com/2015/01/27/a-few-interesting-numbers-about-apache-spark/</link>
		<comments>https://gigaom.com/2015/01/27/a-few-interesting-numbers-about-apache-spark/#comments</comments>
		<pubDate>Tue, 27 Jan 2015 20:00:21 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[Databricks]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[stream processing]]></category>
		<category><![CDATA[Typesafe]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=910109</guid>
		<description><![CDATA[A new survey from startups Databricks and Typesafe revealed some interesting insights into how software developers are using the Apache Spark data-processing framework. Spark is an open source project that has&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2015/01/27/a-few-interesting-numbers-about-apache-spark/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
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		<title>Cloudera tunes Google&#8217;s Dataflow to run on Spark</title>
		<link>https://gigaom.com/2015/01/20/cloudera-tunes-googles-dataflow-to-run-on-spark-clusters/</link>
		<comments>https://gigaom.com/2015/01/20/cloudera-tunes-googles-dataflow-to-run-on-spark-clusters/#comments</comments>
		<pubDate>Tue, 20 Jan 2015 16:16:16 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[batch-processing]]></category>
		<category><![CDATA[Cloud Dataflow]]></category>
		<category><![CDATA[dataflow]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[real-time processing]]></category>
		<category><![CDATA[stream processing]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=907914</guid>
		<description><![CDATA[Hadoop software company Cloudera has worked with Google to make Google's Dataflow programming model run on Apache Spark. Dataflow, which Google announced as a cloud service in June, lets programmers write the same&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2015/01/20/cloudera-tunes-googles-dataflow-to-run-on-spark-clusters/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>The 5 stories that defined the big data market in 2014</title>
		<link>https://gigaom.com/2015/01/02/the-5-stories-that-defined-the-big-data-market-in-2014/</link>
		<comments>https://gigaom.com/2015/01/02/the-5-stories-that-defined-the-big-data-market-in-2014/#comments</comments>
		<pubDate>Fri, 02 Jan 2015 17:27:38 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[deepmind]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Watson]]></category>
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		<guid isPermaLink="false">http://gigaom.com/?p=903494</guid>
		<description><![CDATA[There is no other way to put it: 2014 was a huge year for the big data market. It seems years of talk about what's possible are finally giving way to some&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2015/01/02/the-5-stories-that-defined-the-big-data-market-in-2014/feed/</wfw:commentRss>
		<slash:comments>3</slash:comments>
		</item>
		<item>
		<title>Pivotal and EMC are betting on Spark cousin Tachyon as in-memory file system</title>
		<link>https://gigaom.com/2014/10/14/pivotal-and-emc-are-betting-on-spark-cousin-tachyon-as-in-memory-file-system/</link>
		<comments>https://gigaom.com/2014/10/14/pivotal-and-emc-are-betting-on-spark-cousin-tachyon-as-in-memory-file-system/#comments</comments>
		<pubDate>Tue, 14 Oct 2014 18:47:15 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[AMPLab]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[data lake]]></category>
		<category><![CDATA[in memory processing]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[Tachyon]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NYSE:EMC]]></category>
		
		<guid isPermaLink="false">http://gigaom.com/?p=880773</guid>
		<description><![CDATA[EMC-VMware spinoff Pivotal is putting its money behind Tachyon, an in-memory distributed file system developed by the same research lab that created Apache Spark. The goal is to improve the company's&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/10/14/pivotal-and-emc-are-betting-on-spark-cousin-tachyon-as-in-memory-file-system/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>Databricks demolishes big data benchmark to prove Spark is fast on disk, too</title>
		<link>https://gigaom.com/2014/10/10/databricks-demolishes-big-data-benchmark-to-prove-spark-is-fast-on-disk-too/</link>
		<comments>https://gigaom.com/2014/10/10/databricks-demolishes-big-data-benchmark-to-prove-spark-is-fast-on-disk-too/#comments</comments>
		<pubDate>Fri, 10 Oct 2014 20:49:26 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[Databricks]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[Spark]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=880151</guid>
		<description><![CDATA[Apache Spark is taking the big data world by storm, but the folks at Databricks wanted to disprove a misconception that its only performance advantages over Hadoop MapReduce come in-memory.]]></description>
		<wfw:commentRss>https://gigaom.com/2014/10/10/databricks-demolishes-big-data-benchmark-to-prove-spark-is-fast-on-disk-too/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>Hortonworks lays out a future for Hive that includes transactions, Spark and sub-second queries</title>
		<link>https://gigaom.com/2014/09/03/hortonworks-lays-out-a-future-for-hive-that-includes-transactions-spark-and-sub-second-queries/</link>
		<comments>https://gigaom.com/2014/09/03/hortonworks-lays-out-a-future-for-hive-that-includes-transactions-spark-and-sub-second-queries/#comments</comments>
		<pubDate>Wed, 03 Sep 2014 21:19:57 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Apache Hive]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[SQL on Hadoop]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=869916</guid>
		<description><![CDATA[Hortonworks is working on a new initiative called Stinger.next, which it hopes will remake Apache Hive into a much more-capable SQL engine within the next year and a half. A greatly&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/09/03/hortonworks-lays-out-a-future-for-hive-that-includes-transactions-spark-and-sub-second-queries/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>Adatao takes in $13M to help enterprises understand their data</title>
		<link>https://gigaom.com/2014/08/07/adatao-takes-in-13m-to-help-enterprises-understand-their-data/</link>
		<comments>https://gigaom.com/2014/08/07/adatao-takes-in-13m-to-help-enterprises-understand-their-data/#comments</comments>
		<pubDate>Thu, 07 Aug 2014 14:00:07 +0000</pubDate>
		<dc:creator><![CDATA[Jonathan Vanian]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Apache Spark]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NSDQ:GOOG]]></category>
		
		<guid isPermaLink="false">http://gigaom.com/?p=863375</guid>
		<description><![CDATA[The startup founded by Google and Yahoo engineers uses Apache Spark to power an easy to understand user interface that resembles Google Docs.]]></description>
		<wfw:commentRss>https://gigaom.com/2014/08/07/adatao-takes-in-13m-to-help-enterprises-understand-their-data/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Cloudera: Impala&#8217;s it for interactive SQL on Hadoop; everything else will move to Spark</title>
		<link>https://gigaom.com/2014/07/03/cloudera-impalas-it-for-interactive-sql-on-hadoop-but-everything-else-will-move-to-spark/</link>
		<comments>https://gigaom.com/2014/07/03/cloudera-impalas-it-for-interactive-sql-on-hadoop-but-everything-else-will-move-to-spark/#comments</comments>
		<pubDate>Fri, 04 Jul 2014 00:45:42 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[Impala]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[SQL on Hadoop]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=855468</guid>
		<description><![CDATA[There was a lot of news about Spark's ascension in the big data ranks this week, as well as some speculation. According to Cloudera's Mike Olson, his company is widely embracing&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/07/03/cloudera-impalas-it-for-interactive-sql-on-hadoop-but-everything-else-will-move-to-spark/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>Databricks announces a Spark cloud and $33M in venture capital</title>
		<link>https://gigaom.com/2014/06/30/databricks-announces-a-spark-cloud-and-33m-in-venture-capital/</link>
		<comments>https://gigaom.com/2014/06/30/databricks-announces-a-spark-cloud-and-33m-in-venture-capital/#comments</comments>
		<pubDate>Mon, 30 Jun 2014 17:20:29 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Apache Spark]]></category>
		<category><![CDATA[Databricks]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[Spark]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=854288</guid>
		<description><![CDATA[Big data startup Databricks keeps humming along, announcing on Monday a large round of venture capital and a new cloud service that aims to seed adoption of Spark -- a framework&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/06/30/databricks-announces-a-spark-cloud-and-33m-in-venture-capital/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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