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  [[http://www.meetup.com|Meetup]] is on a mission to help the world’s people 
self-organize into local groups.  We use Hadoop and HBase to power a site-wide, 
real-time activity feed system for all of our members and groups.  Group 
activity is written directly to HBase, and indexed per member, with the 
member's custom feed served directly from HBase for incoming requests.  We're 
running HBase 0.20.0 on a 11 node cluster.
  
  [[http://ning.com|Ning]] uses HBase to store and serve the results of 
processing user events and log files, which allows us to provide near-real time 
analytics and reporting. We use a small cluster of commodity machines with 4 
cores and 16GB of RAM per machine to handle all our analytics and reporting 
needs.
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+ [[http://olex.openlogic.com|OpenLogic]] stores all the world's Open Source 
packages, versions, files, and lines of code in HBase for both near-real-time 
access and analytical purposes.  The production cluster has well over 100TB of 
disk spread across nodes with 32GB+ RAM and dual-quad or dual-hex core CPU's.
  
  [[http://www.openplaces.org|Openplaces]] is a search engine for travel that 
uses HBase to store terabytes of web pages and travel-related entity records 
(countries, cities, hotels, etc.). We have dozens of MapReduce jobs that crunch 
data on a daily basis.  We use a 20-node cluster for development, a 40-node 
cluster for offline production processing and an EC2 cluster for the live web 
site.
  

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