cannot join on column with datetime when using the 'on' parameter
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd

left = pd.DataFrame({'date':['2019-01-01'], 'a': [1]})
left['date'] = pd.to_datetime(left['date'], utc=True)

right = pd.DataFrame({'date':['2019-01-01'], 'b': [1]})
right['date'] = pd.to_datetime(right['date'], utc=True)

# execption
left.join(right, on='date')
```
#### Problem description
```
ValueError: You are trying to merge on datetime64[ns, UTC] and int64 columns. If you wish to proceed you should use pd.concat
```
Both column have the same dtype when calling join, somehow the right join colum gets converted to int64. This causes the join to fail.
However, the follwing code works fine:
``` python
# init as above
left = left.set_index('date')
right = right.set_index('date')
left.join(right)
"""
                           a  b
date                           
2019-01-01 00:00:00+00:00  1  1

"""
```

#### Expected Output

```
date                       a  b                           
2019-01-01 00:00:00+00:00  1  1
```

#### Output of ``pd.show_versions()``

<details>
commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.15.0-54-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: de_DE.UTF-8
LOCALE: de_DE.UTF-8

pandas: 0.24.2
pytest: 4.3.1
pip: 10.0.1
setuptools: 39.1.0
Cython: None
numpy: 1.16.4
scipy: None
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
