`read_sql_table` fails on Geopackge SQLite file due to DATETIME field with string value
#### Code Sample, a copy-pastable example if possible

```python
import sqlite3
import pandas as pd

con = sqlite3.connect("tmp.db")
c = con.cursor()
c.execute("CREATE TABLE gpkg_contents (last_change DATETIME);")
c.execute("INSERT INTO gpkg_contents VALUES ('2019-01-01T00:00:00.000Z');")
con.commit()
con.close()
df = pd.read_sql_table(
    "gpkg_contents",
    "sqlite:///tmp.db",
    parse_dates=["last_change"]
)
df["last_change"][0]
```

#### Problem description

The above minimal example raises the following error:


```pytb
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-172-a1e2291991c6> in <module>
      6 con.commit()
      7 con.close()
----> 8 df = pd.read_sql_table("gpkg_contents", "sqlite:///tmp.db", parse_dates=["last_change"])
      9 df["last_change"][0]

~/.venv/lib/python3.7/site-packages/pandas/io/sql.py in read_sql_table(table_name, con, schema, index_col, coerce_float, parse_dates, columns, chunksize)
    252         parse_dates=parse_dates,
    253         columns=columns,
--> 254         chunksize=chunksize,
    255     )
    256 

~/.venv/lib/python3.7/site-packages/pandas/io/sql.py in read_table(self, table_name, index_col, coerce_float, parse_dates, columns, schema, chunksize)
   1143             parse_dates=parse_dates,
   1144             columns=columns,
-> 1145             chunksize=chunksize,
   1146         )
   1147 

~/.venv/lib/python3.7/site-packages/pandas/io/sql.py in read(self, coerce_float, parse_dates, columns, chunksize)
    803             data = result.fetchall()
    804             self.frame = DataFrame.from_records(
--> 805                 data, columns=column_names, coerce_float=coerce_float
    806             )
    807 

~/.venv/lib/python3.7/site-packages/pandas/core/frame.py in from_records(cls, data, index, exclude, columns, coerce_float, nrows)
   1611             arr_columns = columns
   1612         else:
-> 1613             arrays, arr_columns = to_arrays(data, columns, coerce_float=coerce_float)
   1614 
   1615             arr_columns = ensure_index(arr_columns)

~/.venv/lib/python3.7/site-packages/pandas/core/internals/construction.py in to_arrays(data, columns, coerce_float, dtype)
    485     else:
    486         # last ditch effort
--> 487         data = [tuple(x) for x in data]
    488         return _list_to_arrays(data, columns, coerce_float=coerce_float, dtype=dtype)
    489 

~/.venv/lib/python3.7/site-packages/pandas/core/internals/construction.py in <listcomp>(.0)
    485     else:
    486         # last ditch effort
--> 487         data = [tuple(x) for x in data]
    488         return _list_to_arrays(data, columns, coerce_float=coerce_float, dtype=dtype)
    489 
ValueError: Couldn't parse datetime string: '2019-01-01T00:00:00.000Z
```

Surprisingly, using

```python
pd.read_sql_query("SELECT * FROM gpkg_contents", ...)
```

instead of `read_sql_table` does give exactly the expected result.

As the table name suggests, I encountered this bug when working on a Geopackage file, that uses a `CREATE` statement with `DATETIME` type and string values as per the [format specification](http://www.geopackage.org/spec/) and this is thus implemented as such in many GIS tools.

#### Expected Output

```python
Timestamp('2019-01-01 00:00:00+0000', tz='UTC')
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.3.0-24-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : de_DE.UTF-8
LOCALE           : de_DE.UTF-8

pandas           : 0.25.3
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 44.0.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.11.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.2
numexpr          : None
odfpy            : None
openpyxl         : 3.0.2
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.12
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
</details>
