Performance degradation appending rows to sqlite
Hey folks --

I'm writing a large CSV (100M rows) to a sqlite database through Pandas in 10k chunks.

```
disk_engine = create_engine('sqlite:///100M.db')
chunksize = 10000
index_start = 0
for df in pd.read_csv('100M_rows.csv', chunksize=chunksize, iterator=True, encoding='utf-8'):
    df.index += index_start
    df.to_sql('data', disk_engine, if_exists='append')
    index_start = df.index[-1] + 1
```

I'm seeing non-linear writing speeds after writing 1M rows: 
![](https://plot.ly/~chris/7407.png)

Is there a more efficient way I should be writing these appends? Many thanks!
