title: Django + Postgres + Large Time Series
body: <p>I am scoping out a project with large, mostly-uncompressible time series data, and wondering if Django + Postgres with raw SQL is the right call.</p>
  
  <p>I have time series data that is ~2K objects/hour, every hour.  This is about 2 million rows per year I store, and I would like to 1) be able to slice off data for analysis through a connection, 2) be able to do elementary overview work on the web, served by Django.  I think the best idea is to use Django for the objects themselves, but drop to raw SQL to deal with the large time series data associated.  I see this as a hybrid approach; that might be a red flag, but using the full ORM for a long series of data samples feels like overkill.  Is there a better way?</p>