How to transform a huge CSV into SQLite using Pandas?

I have a huge table (about 60 GB) in form of an archived CSV file. I want to transform it into an SQLite file.

What I do at the moment in the following:

import pandas
import sqlite3
cnx = sqlite3.connect('db.sqlite')
df = pandas.read_csv('db.gz', compression='gzip')
df.to_sql('table_name', cnx)

It works fine for smaller files but with the huge files I have memory problem. The problem is that pandas reads the whole table into memory (RAM) and then saves it into SQLite file.

Is there an elegant solution to this problem?