title: pandas .to_sql timing out with RDS
body: <p>I have a 22 million row .csv file (~850mb) that I am trying to load into a postgres db on Amazon RDS. It fails every time (I get a time-out error), even when I split the file into smaller parts (each of 100,000 rows) and even when I use <code>chunksize</code>.</p>
  
  <p>All I am doing at the moment is loading the .csv as a dataframe and then writing it to the db using <code>df.to_sql(table_name, engine, index=False, if_exists='append', chunksize=1000)</code> </p>
  
  <p>I am using create_engine from sqlalchemy to create the connection: <code>engine = create_engine('postgresql:database_info')</code></p>
  
  <p>I have tested writing smaller amounts of data with <code>psycopg2</code> without a problem, but it takes around 50 seconds to write 1000 rows. Obviously for 22m rows that won't work.</p>
  
  <p>Is there anything else I can try?</p>