Reading table with chunksize still pumps the memory
I'm trying to migrate database tables from MySQL to SQL Server:

``` python
import pandas as pd
from sqlalchemy import create_engine

my_engine = create_engine("mysql+pymysql://root:pass@localhost/gen")
ms_engine = create_engine('mssql+pyodbc://localhost/gen?driver=SQL Server')

for table_name in ['topics', 'fiction', 'compact']:
    for table in pd.read_sql_query('SELECT * FROM %s' % table_name,
                                   my_engine, 
                                   chunksize=100000):

        table.to_sql(name=table_name, con=ms_engine, if_exists='append')
```

I thought that using chunksize would release the memory, but it's just growing up.
I tried also garbage collector, but it has no effect.

Maybe my expectations were wrong?

_I'm using Python 3.5.1 with pandas 0.17.1 and all latest packages, although I tried also Python 2.7 with pandas 0.16 and same results_ 
