svn commit: r1597367 - /incubator/storm/site/documentation/Powered-By.md

[na...@apache.org]

Author: nathanmarz
Date: Sun May 25 01:53:38 2014
New Revision: 1597367

URL: http://svn.apache.org/r1597367
Log:
added companies to powered by page

Modified:
    incubator/storm/site/documentation/Powered-By.md

Modified: incubator/storm/site/documentation/Powered-By.md
URL: http://svn.apache.org/viewvc/incubator/storm/site/documentation/Powered-By.md?rev=1597367&r1=1597366&r2=1597367&view=diff
==============================================================================
--- incubator/storm/site/documentation/Powered-By.md (original)
+++ incubator/storm/site/documentation/Powered-By.md Sun May 25 01:53:38 2014
@@ -58,6 +58,20 @@ Yahoo! is developing a next generation p
 
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+<a href="http://www.webmd.com">WebMD</a>
+</td>
+<td>
+<p>
+We use Storm to power our Medscape Medpulse mobile application which allow medical professionals to follow important medical trends with Medscape's curated Today on Twitter feed and selection of blogs. Storm topology is capturing and processing tweets with twitter streaming API, enhance tweets with metadata and images, do real time NLP and execute several business rules. Storm also monitors selection of blogs in order to give our customers real-time updates.  We also use Storm for internal data pipelines to do ETL and for our internal marketing platform where time and freshness are essential.
+</p>
+<p>
+We use storm to power our search indexing process.  We continue to discover new use cases for storm and it became one of the core component in our technology stack.
+</p>
+</td>
+</tr>
+
+<tr>
+<td>
 <a href="http://www.infochimps.com">Infochimps</a>
 </td>
 <td>
@@ -726,7 +740,67 @@ At OpenX we use Storm to process large a
 </td>
 <td>
 <p>
-"Keen IO is an analytics backend-as-a-service. The Keen IO API makes it easy for customers to do internal analytics or expose analytics features to their customers. Keen IO uses Storm (DRPC) to query billion-event data sets at very low latencies. We also use Storm to control our ingestion pipeline, sourcing data from Kafka and storing it in Cassandra.
+Keen IO is an analytics backend-as-a-service. The Keen IO API makes it easy for customers to do internal analytics or expose analytics features to their customers. Keen IO uses Storm (DRPC) to query billion-event data sets at very low latencies. We also use Storm to control our ingestion pipeline, sourcing data from Kafka and storing it in Cassandra.
+</p>
+</td>
+</tr>
+
+<tr>
+<td>
+<a href="http://liveperson.com/">LivePerson</a>
+</td>
+<td>
+<p>
+LivePerson is a provider of Interaction-Service over the web. Interaction between an agent and a visitor in site can be achieved using phone call, chat, banners, etc.Using Storm, LivePerson can collect and process visitor data and provide information in real time to the agents about the visitor behavior. Moreover, LivePerson gets to better decisions about how to react to visitors in a way that best addresses their needs.
+</p>
+</td>
+</tr>
+
+<tr>
+<td>
+<a href="http://yieldbot.com/">YieldBot</a>
+</td>
+<td>
+<p>
+Yieldbot connects ads to the real-time consumer intent streaming within premium publishers. To do this, Yieldbot leverages Storm for a wide variety of real-time processing tasks. We've open sourced our clojure DSL for writing trident topologies, marceline, which we use extensively. Events are read from Kafka, most state is stored in Cassandra, and we heavily use Storm's DRPC features. Our Storm use cases range from HTML processing, to hotness-style trending, to probabilistic rankings and cardinalities. Storm topologies touch virtually all of the events generated by the Yieldbot platform.
+</p>
+</td>
+</tr>
+
+<tr>
+<td>
+<a href="http://equinix.com/">Equinix</a>
+</td>
+<td>
+<p>
+At Equinix, we use a number of Storm topologies to process and persist various data streams generated by sensors in our data centers. We also use Storm for real-time monitoring of different infrastructure components. Other few topologies are used for processing logs in real-time for internal IT systems  which also provide insights in user behavior.
+</p>
+</td>
+</tr>
+
+
+<tr>
+<td>
+<a href="http://minewhat.com/">MineWhat</a>
+</td>
+<td>
+<p>
+MineWhat provides actionable analytics for ecommerce spanning every SKU,brand and category in the store. We use Storm to process raw click stream ingestion from Kafka and compute live analytics. Storm topologies powers our complex product to user interaction analysis. Multi language feature in storm is really kick-ass, we have bolts written in Node.js, Python and Ruby. Storm has been in our production site since Nov 2012.
+</p>
+</td>
+</tr>
+
+
+<tr>
+<td>
+<a href="http://www.360.cn/">Qihoo 360</a>
+</td>
+<td>
+<p>
+360 have deployed about 50 realtime applications on top of storm including web page analysis, log processing, image processing, voice processing, etc.
+</p>
+<p>
+The use case of storm at 360 is a bit special since we deployed storm on thounds of servers which are not dedicated for storm. Storm just use little cpu/memory/network resource on each server. However theses storm clusters leverage idle resources of servers at nearly zero cost to provide great computing power and it's realtime. It's amazing.
 </p>
 </td>
 </tr>