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	<title>Gigaom Search &#187; Companies &#187; Databricks</title>
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		<title>Apache Big Data releases continue unabated</title>
		<link>http://research.gigaom.com/2015/03/apache-big-data-releases-continue-unabated/</link>
		<comments>http://research.gigaom.com/2015/03/apache-big-data-releases-continue-unabated/#comments</comments>
		<pubDate>Wed, 04 Mar 2015 14:00:10 +0000</pubDate>
		<dc:creator><![CDATA[Andrew Brust]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[new releases]]></category>

		<guid isPermaLink="false">http://research.gigaom.com/?p=246381</guid>
		<description><![CDATA[Last week, I wrote briefly about Apache HBase pushing out its 1.0 release. Subsequently, news of several more new releases of Big Data-related projects rolled out of the Apache Software Foundation. I&#8230;]]></description>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<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>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:INTC]]></category>
		<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:MSFT]]></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>
		<item>
		<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>
		<item>
		<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>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:GOOG]]></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>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:GOOG]]></category>
		<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:MSFT]]></category>
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		<category domain="http://search.gigaom.com/stock/"><![CDATA[NYSE:IBM]]></category>
		<category domain="http://search.gigaom.com/stock/"><![CDATA[NYSE:TWTR]]></category>
		
		<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>Cloud computing is going to absorb your big data workloads, too</title>
		<link>https://gigaom.com/2014/10/15/cloud-computing-is-going-to-absorb-your-big-data-workloads-too/</link>
		<comments>https://gigaom.com/2014/10/15/cloud-computing-is-going-to-absorb-your-big-data-workloads-too/#comments</comments>
		<pubDate>Wed, 15 Oct 2014 23:22:00 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[open source]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:MSFT]]></category>
		<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:ORCL]]></category>
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		<category domain="http://search.gigaom.com/stock/"><![CDATA[NYSE:RAX]]></category>
		
		<guid isPermaLink="false">http://gigaom.com/?p=881183</guid>
		<description><![CDATA[There has been a spate of product announcements and integrations over the past few weeks signaling that many big data workloads -- including, and especially, Hadoop -- will soon be ready&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/10/15/cloud-computing-is-going-to-absorb-your-big-data-workloads-too/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>Predictive analytics and data-blending specialist Alteryx raises $60M</title>
		<link>https://gigaom.com/2014/10/06/predictive-analytics-and-data-blending-specialist-alteryx-raises-60m/</link>
		<comments>https://gigaom.com/2014/10/06/predictive-analytics-and-data-blending-specialist-alteryx-raises-60m/#comments</comments>
		<pubDate>Mon, 06 Oct 2014 14:58:39 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Alteryx]]></category>
		<category><![CDATA[in memory processing]]></category>
		<category><![CDATA[predictive analytics]]></category>
		<category><![CDATA[predictive modeling]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=878551</guid>
		<description><![CDATA[Alteryx has raised $60 million to help expand its fast-growing business, which straddles the middle ground between Excel and SPSS by trying to turn data blending and predictive modeling into self-service experiences.]]></description>
		<wfw:commentRss>https://gigaom.com/2014/10/06/predictive-analytics-and-data-blending-specialist-alteryx-raises-60m/feed/</wfw:commentRss>
		<slash:comments>0</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>The lab that created Spark wants to speed up everything, including cures for cancer</title>
		<link>https://gigaom.com/2014/08/02/the-lab-that-created-spark-wants-to-speed-up-everything-including-cures-for-cancer/</link>
		<comments>https://gigaom.com/2014/08/02/the-lab-that-created-spark-wants-to-speed-up-everything-including-cures-for-cancer/#comments</comments>
		<pubDate>Sat, 02 Aug 2014 16:30:39 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[AMPLab]]></category>
		<category><![CDATA[genetic research]]></category>
		<category><![CDATA[Mesos]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[Spark]]></category>
		<category><![CDATA[SQL on Hadoop]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=861725</guid>
		<description><![CDATA[AMPLab, the University of California, Berkeley, research group responsible for making Spark a household name in big data, has a lot more tricks up its sleeve. They range from databases to&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/08/02/the-lab-that-created-spark-wants-to-speed-up-everything-including-cures-for-cancer/feed/</wfw:commentRss>
		<slash:comments>3</slash:comments>
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