title: Elasticsearch sync database recommended / standard strategy
body: <p>I'm pondering a strategy to maintain an index for Elasticsearch, I've found a <a href="https://github.com/jprante/elasticsearch-river-jdbc" rel="noreferrer">plugin</a> which may handle maintenance quite well however I would like to get a little more intimate with Elasticsearch since I really like her and the plugin would make playtime a little less intimate if you know what I mean.</p>
  
  <p>So anyway, if I have a data set that would have fairly frequent updates (say ~ 1 update / 10s), would I run into performance problems with Elasticsearch? Can partial index updates be done when a single row changes or is a full re-rebuild of the index necessary? The strategy I plan on implementing involves modifying the index whenever I do CRUD with my application (python postgre) so there will be some overhead with the code which I'm not overly concerned about, just the performance. Is my strategy common?</p>
  
  <p>I've used Sphinx which did have partial re-indexing which was run with a cron job to keep in sync, it had mapping between indexes and MySQL tables defined in the config. This was the recommended approach for Sphinx. Is there a recommended approach with Elasticsearch?</p>