BUG: pd.compare does not recognize differences when comparing values with null Int64 data type
in  `pd.compare` if any comparisons result in `null` values like `pd.NA`, consider the values unequal. 


- [x] closes #48939 (Replace xxxx with the Github issue number)
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [x] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [x] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.

do I need to change anything or the cancelled check will be rerun? Hi @phofl 

seems like `compare` considers all missing values the same. 
Considering this is the current behavior of the method, can we go ahead?

```Python console
In [57]: df2 = pd.DataFrame({'a': pd.Series([4, np.nan]), 'b': [3, pd.NaT] })

In [58]: df1 = pd.DataFrame({'a': pd.Series([4, pd.NaT]), 'b': [3, np.nan] })

In [59]: df1.compare(df2)
Out[59]:
Empty DataFrame
Columns: []
Index: []
```

Also, something to note - `equals` considers two `pd.NA`s the same.

```Python console
In [61]: df1 = pd.DataFrame({'a': pd.Series([4, pd.NA], dtype='Int64'), 'b': [3, pd.NA] })

In [62]: df2 = pd.DataFrame({'a': pd.Series([4, pd.NA], dtype='Int64'), 'b': [3, pd.NA] })

In [63]: df1.equals(df2)
Out[63]: True
```


 Don't know why the test failed in ubuntu. the test passes for me on WSL. Thx @vamsi-verma-s 