title: Cassandra performance updating rows over time
body: <p>I am trying to determine how suitable Cassandra is for my application, as it is unknown how much we will need to scale in the future and could occur rapidly.  I have been watching various segments of the C* Summit 2013.  </p>
  
  <p>Specifically, Axel Liljencrantz, Backend Developer at Spotify, <a href="http://www.youtube.com/watch?feature=player_detailpage&amp;v=0u-EKJBPrj8#t=578" rel="nofollow">says here</a> that you can expect Cassandra performance to degrade over time if your model requires you to update the same row over and over.  </p>
  
  <p>My model requirement is a "document store" kind of type with known fields, with values that change over a number of months, as it meets various real-life requirements/status points.  Various queries and counts need to be performed across different kinds of documents stored.</p>
  
  <p>So: Are there any suitable ways to mitigate this, if all documents have typically the same known average life-time before they remained fixed, historical data?</p>
  
  <p>Is it ill-conceived to work around this by storing a version number and rewriting the whole document to a new row as information is updated?</p>