Columns names outputs are inconsistents and case sensitive

### What happens?

Output of the code block:
```shell
PS C:\Users\tibo\python_codes\pql> uv run t.py
relation.columns: ['foo', 'Foo']
to_arrow_table: ['foo', 'Foo']
pl.from_arrow: ['foo', 'Foo']
relation.pl eager: ['foo', 'Foo_1']
relation.pl lazy: ['foo', 'Foo']
pandas result: ['foo', 'Foo_1']
arrow query result: ['foo', 'Foo']
PS C:\Users\tibo\python_codes\pql>
```

pandas and polars dataframe don't give the same results as the rest.

### To Reproduce

```python
import duckdb
import polars as pl

rel = duckdb.from_query("select 1 as foo, 2 as Foo")

print("relation.columns:", rel.columns)
print("to_arrow_table:", rel.to_arrow_table().column_names)
print("pl.from_arrow:", pl.from_arrow(rel.to_arrow_table()).columns)
print("relation.pl eager:", rel.pl().columns)
print("relation.pl lazy:", rel.pl(lazy=True).collect().columns)
print("pandas result:", list(rel.df().columns))
print("arrow query result:", rel.to_arrow_reader().read_all().column_names)
```

### OS:

Windows

### DuckDB Package Version:

1.5.1

### Python Version:

3.13.7

### Full Name:

Stettler Thibaud

### Affiliation:

University of Geneva

### What is the latest build you tested with? If possible, we recommend testing with the latest nightly build.

`1.5.2.dev40`

### Did you include all relevant data sets for reproducing the issue?

Yes

### Did you include all code required to reproduce the issue?

- [x] Yes, I have

### Did you include all relevant configuration to reproduce the issue?

- [x] Yes, I have

Start by running the supplied Python reproduction against the current DuckDB Python package and compare rel.pl(), rel.df(), the Arrow conversions, and the lazy result. Trace the Python relation-to-Polars and relation-to-pandas entry points, then add or update regression coverage so equivalent outputs handle the case-variant columns consistently.

Written by the indexing model from the issue text.