title: Database choice for stock data
body: <p>I'm wondering if NoSQL is an option for this scenario:</p>
  
  <p>The input are hourly stock data (<a href="http://en.wikipedia.org/wiki/Stock-keeping_unit" rel="nofollow">sku</a>, amount, price and some more specific) from several sources. Older versions will just get droped. So we won't get over 1 mio. data sets in the near future and there won't be any business intelligence queries like in data warehouses. But there will be <strong>aggregations</strong>, at least for the <strong>minimal price of a group</strong> of articles which has to get updated if the article with the minimal price of a group is sold out. In addition to these bulk writes on a frequent base there will be single decrements on the amount of an article which can happen at any time.</p>
  
  <p>The database would be part of a service which needs to give fast responses to requests via REST. So there needs to be some kind of caching. There is no need for stong consistency, but durabiltity.</p>
  
  <p>Further wishlist:</p>
  
  <ul>
  <li>should scale well for growing request load</li>
  <li>inexpensive technologies in terms of money and complexity (no Oracle cluster)</li>
  <li>no proprietary languages (no PL/SQL)</li>
  </ul>
  
  <p>MongoDB with its <a href="http://www.mongodb.org/display/DOCS/Aggregation+Framework+-+%24group" rel="nofollow">aggregation framework</a> seems promising. Can you think of alteratives? (I do not stick to NoSQL!)</p>