<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>VoltDB Blog &#187; Mike Stonebraker</title>
	<atom:link href="http://blog.voltdb.com/author/mstonebraker-wp/feed/" rel="self" type="application/rss+xml" />
	<link>http://blog.voltdb.com</link>
	<description>VoltDB Blog</description>
	<lastBuildDate>Tue, 07 May 2013 21:53:46 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>hourly</sy:updatePeriod>
	<sy:updateFrequency>1</sy:updateFrequency>
	<generator>http://wordpress.org/?v=3.4.2</generator>
		<item>
		<title>To Flash or Not to Flash: That is the Question</title>
		<link>http://blog.voltdb.com/to-flash-or-not-to-flash-that-is-the-question/</link>
		<comments>http://blog.voltdb.com/to-flash-or-not-to-flash-that-is-the-question/#comments</comments>
		<pubDate>Tue, 12 Jun 2012 14:46:53 +0000</pubDate>
		<dc:creator>Mike Stonebraker</dc:creator>
				<category><![CDATA[Best Practices]]></category>
		<category><![CDATA[NewSQL]]></category>
		<category><![CDATA[Deployment Management]]></category>
		<category><![CDATA[Durability]]></category>
		<category><![CDATA[High Availability]]></category>

		<guid isPermaLink="false">http://newblog.voltdb.com/?p=80</guid>
		<description><![CDATA[<p>I am often asked about the value of flash memory in OLTP database applications.  This blog post discusses flash technology in this context.  First, I discuss the future of flash in general; then I turn to flash (and other future storage technologies) in the context of a main memory DBMS, such as <a href="http://www.voltdb.com/tao-volt/products-solutions.php" data-cke-saved-href="http://voltdb.com/products-services/products">VoltDB</a>.</p>
<h3>The Future of Flash</h3>
<p>Flash memory is clearly a “moving window”, since its price and performance are changing quickly.  Historically, flash could only be written a few thousand times, before it would “wear out” and have to be replaced.  This drawback seems to have been eliminated &#8230; <a href="http://blog.voltdb.com/to-flash-or-not-to-flash-that-is-the-question/" class="read_more">Read more</a></p>]]></description>
		<wfw:commentRss>http://blog.voltdb.com/to-flash-or-not-to-flash-that-is-the-question/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>OLTP and Decision Support</title>
		<link>http://blog.voltdb.com/oltp-and-decision-support/</link>
		<comments>http://blog.voltdb.com/oltp-and-decision-support/#comments</comments>
		<pubDate>Tue, 01 May 2012 14:29:47 +0000</pubDate>
		<dc:creator>Mike Stonebraker</dc:creator>
				<category><![CDATA[Best Practices]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[NewSQL]]></category>
		<category><![CDATA[OLTP]]></category>
		<category><![CDATA[Real-time Analytics]]></category>
		<category><![CDATA[OLAP and Hadoop]]></category>

		<guid isPermaLink="false">http://newblog.voltdb.com/?p=62</guid>
		<description><![CDATA[<p>The purpose of this blog posting is to discuss strategies for handling decision support queries in Online Transaction Processing (OLTP) applications.  First, I want to talk about the two classes of OLTP applications that I see in the marketplace.</p>
<p>The first is the <strong>traditional </strong>OLTP market that has been present for years, and is typified by purchasing Wall Street stocks.  A collection of humans (stock brokers or end-users over the web) interact with an OLTP system to trade securities.  The brokerage house (and end users for that matter) also want to run decision support queries to learn about historical trends &#8230; <a href="http://blog.voltdb.com/oltp-and-decision-support/" class="read_more">Read more</a></p>]]></description>
		<wfw:commentRss>http://blog.voltdb.com/oltp-and-decision-support/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>Q&amp;A from March 21 Webinar</title>
		<link>http://blog.voltdb.com/qa-march-21-webinar/</link>
		<comments>http://blog.voltdb.com/qa-march-21-webinar/#comments</comments>
		<pubDate>Mon, 26 Mar 2012 12:39:02 +0000</pubDate>
		<dc:creator>Mike Stonebraker</dc:creator>
				<category><![CDATA[Best Practices]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[NewSQL]]></category>
		<category><![CDATA[OLTP]]></category>
		<category><![CDATA[Real-time Analytics]]></category>

		<guid isPermaLink="false">http://newblog.voltdb.com/?p=28</guid>
		<description><![CDATA[<p>Last week I gave a webinar entitled <em>OldSQL vs. NoSQL vs. NewSQL for New OLTP.</em>  If you missed the live webinar and want to view the recorded version, you&#8217;ll find it <a href="http://www.voltdb.com/dig-deeper/multimedia/webinars.php" data-cke-saved-href="http://voltdb.com/resources/webinars">here</a> (you may need to scroll down to find it).  Below is a list of questions that live webinar attendees asked, in no particular order.  If you have follow-on questions, reply to this post and I or someone else from VoltDB will answer them.<img title="&#60;--break--&#62;" src="https://voltdb.com/sites/all/modules/wysiwyg/plugins/break/images/spacer.gif" alt="&#60;--break-&#62;" data-cke-saved-src="/sites/all/modules/wysiwyg/plugins/break/images/spacer.gif" /></p>
<h3>Webinar Questions and Answers</h3>
<p>1.<em>  Does VoltDB run on Scale up NUMA like systems or is it designed primarily to run on scale out clusters?</em>&#8230; <a href="http://blog.voltdb.com/qa-march-21-webinar/" class="read_more">Read more</a></p>]]></description>
		<wfw:commentRss>http://blog.voltdb.com/qa-march-21-webinar/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Use Main Memory for OLTP</title>
		<link>http://blog.voltdb.com/use-main-memory-oltp/</link>
		<comments>http://blog.voltdb.com/use-main-memory-oltp/#comments</comments>
		<pubDate>Thu, 22 Mar 2012 12:31:59 +0000</pubDate>
		<dc:creator>Mike Stonebraker</dc:creator>
				<category><![CDATA[Best Practices]]></category>
		<category><![CDATA[Big Data]]></category>
		<category><![CDATA[OLTP]]></category>
		<category><![CDATA[Real-time Analytics]]></category>

		<guid isPermaLink="false">http://newblog.voltdb.com/?p=21</guid>
		<description><![CDATA[<p>This is the first in a series of blog posts in which I will explore various aspects of On-Line Transaction Processing (OLTP).   In this post, I&#8217;ll examine main memory storage as an alternative to disk for traditional and “New OLTP” systems.</p>
<p>Traditional relational DBMSs, Hadoop and most of the NoSQL offerings store their data on disk.  In contrast, VoltDB is a main memory DBMS.</p>
<p>First, it should be noted that main memory is getting very cheap.  It is straightforward to put 50 Gbytes of memory on a $5,000 server.  Beefy servers these days have 10 times that amount. Moreover, many &#8230; <a href="http://blog.voltdb.com/use-main-memory-oltp/" class="read_more">Read more</a></p>]]></description>
		<wfw:commentRss>http://blog.voltdb.com/use-main-memory-oltp/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Clarifications on the CAP Theorem and Data-Related Errors</title>
		<link>http://blog.voltdb.com/clarifications-cap-theorem-and-data-related-errors/</link>
		<comments>http://blog.voltdb.com/clarifications-cap-theorem-and-data-related-errors/#comments</comments>
		<pubDate>Thu, 21 Oct 2010 20:48:38 +0000</pubDate>
		<dc:creator>Mike Stonebraker</dc:creator>
				<category><![CDATA[VoltDB Products]]></category>
		<category><![CDATA[VoltDB Products/Versions]]></category>

		<guid isPermaLink="false">http://newblog.voltdb.com/?p=243</guid>
		<description><![CDATA[<div>
<div>There has been another round of online conversations about the CAP theorem as the internet community continues to discuss its implications on networked databases.   Coda Hale recently wrote a well received article titled, <a href="http://codahale.com/you-cant-sacrifice-partition-tolerance/" data-cke-saved-href="http://codahale.com/you-cant-sacrifice-partition-tolerance/" data-cke-pa-onclick="window.open(this.href, '', 'resizable=yes,status=no,location=no,toolbar=no,menubar=yes,fullscreen=no,scrollbars=yes,dependent=no,width=1000,left=450'); return false;">&#8220;You Can&#8217;t Sacrifice Partition Tolerance&#8221;</a>, acknowledged as <a href="http://twitter.com/eric_brewer/status/26819094612" data-cke-saved-href="http://twitter.com/eric_brewer/status/26819094612" data-cke-pa-onclick="window.open(this.href, '', 'resizable=yes,status=no,location=no,toolbar=no,menubar=yes,fullscreen=no,scrollbars=yes,dependent=no,width=1000,left=450'); return false;">&#8220;pretty good&#8221;</a> by Eric Brewer.  Coda refers extensively to the <a href="http://www.google.com/url?sa=t&#38;source=web&#38;cd=1&#38;ved=0CBgQFjAA&#38;url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.67.6951%26rep%3Drep1%26type%3Dpdf&#38;rct=j&#38;q=brewer%27s%20conjecture%20and%20the%20feasibility%20of%20consistent&#38;ei=JJzATJCqO8GC8gbBiIHvBA&#38;usg=AFQjCNHinLgx73mkiiTjwI6f5ySYKzHIdw&#38;cad=rja" data-cke-saved-href="http://www.google.com/url?sa=t&#38;source=web&#38;cd=1&#38;ved=0CBgQFjAA&#38;url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.67.6951%26rep%3Drep1%26type%3Dpdf&#38;rct=j&#38;q=brewer%27s%20conjecture%20and%20the%20feasibility%20of%20consistent&#38;ei=JJzATJCqO8GC8gbBiIHvBA&#38;usg=AFQjCNHinLgx73mkiiTjwI6f5ySYKzHIdw&#38;cad=rja" data-cke-pa-onclick="window.open(this.href, '', 'resizable=yes,status=no,location=no,toolbar=no,menubar=yes,fullscreen=no,scrollbars=yes,dependent=no,width=1000,left=450'); return false;">CAP paper by Gilbert and Lynch</a>.</div>
</div>
<p>Scattered in the larger conversation is a continued mis-perception of my position regarding the CAP theorem. Coda writes &#8220;Michael Stonebraker&#8217;s assertion aside, partitions (read: failures) do happen.&#8221; Others have made similar comments, so let me set the record straight.</p>
<p>I have consistently &#8230; <a href="http://blog.voltdb.com/clarifications-cap-theorem-and-data-related-errors/" class="read_more">Read more</a></p>]]></description>
		<wfw:commentRss>http://blog.voltdb.com/clarifications-cap-theorem-and-data-related-errors/feed/</wfw:commentRss>
		<slash:comments>13</slash:comments>
		</item>
	</channel>
</rss>
