Slow MySQL Connections since switch to SQLAlchemy
I'm coming from version 0.13 to 0.14 and testing out querying a database with the new SQLAlchemy back-end. I'm seeing some exceptionally slow behavior. Consider:

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

query = "select count(*) from transactions where started > '2014-08-29'"
engine = create_engine('mysql+mysqlconnector://myuser:mypass@db_host/db')
df = pd.read_sql_query(query, engine)
```

The query above executes in less than a second with pandas 0.13. It now takes more than 30 seconds. I've monitored the MySQL server and the query is not in the process list during this extra time. So something in the middle is getting stuck.

If I change that to:

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

query = "select count(*) from transactions where started > '2014-08-29'"
engine = create_engine('mysql+mysqlconnector://myuser:mypass@db_host/db')
connection = engine.raw_connection()
df = pd.read_sql_query(query, connection)
```

The query only takes 2-3 seconds. I arrived at this speed-up through lots of trial and error. Why is this faster?

Here's my current setup (it's the Anaconda Python 3.4 distribution, but I get the same thing with their Python 2.7 distribution. It also doesn't seem to matter if I'm using MySQLdb our mysql-connector):
## INSTALLED VERSIONS

commit: None
python: 3.4.1.final.0
python-bits: 64
OS: Darwin
OS-release: 13.3.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.14.0
nose: 1.3.3
Cython: 0.20.1
numpy: 1.8.1
scipy: 0.14.0
statsmodels: None
IPython: 2.1.0
sphinx: 1.2.2
patsy: 0.2.1
scikits.timeseries: None
dateutil: 2.1
pytz: 2014.3
bottleneck: None
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.3.1
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.5.5
lxml: 3.3.5
bs4: 4.3.1
html5lib: None
bq: None
apiclient: None
rpy2: None
sqlalchemy: 0.9.4
pymysql: None
psycopg2: None
