diff --git a/doc/source/getting_started/comparison/comparison_with_sql.rst b/doc/source/getting_started/comparison/comparison_with_sql.rst
index 49a21f87382b3..0596687b4d15e 100644
--- a/doc/source/getting_started/comparison/comparison_with_sql.rst
+++ b/doc/source/getting_started/comparison/comparison_with_sql.rst
@@ -233,6 +233,12 @@ default, :meth:`~pandas.DataFrame.join` will join the DataFrames on their indice
 parameters allowing you to specify the type of join to perform (``LEFT``, ``RIGHT``, ``INNER``,
 ``FULL``) or the columns to join on (column names or indices).
 
+.. warning::
+
+    If both key columns contain rows where the key is a null value, those
+    rows will be matched against each other. This is different from usual SQL
+    join behaviour and can lead to unexpected results.
+
 .. ipython:: python
 
     df1 = pd.DataFrame({"key": ["A", "B", "C", "D"], "value": np.random.randn(4)})
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 48b18a33f9c9f..cfb9740f8c988 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -265,6 +265,12 @@
 When performing a cross merge, no column specifications to merge on are
 allowed.
 
+.. warning::
+
+    If both key columns contain rows where the key is a null value, those
+    rows will be matched against each other. This is different from usual SQL
+    join behaviour and can lead to unexpected results.
+
 Parameters
 ----------%s
 right : DataFrame or named Series