diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 312f5d20d794f..43003553d7ad6 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -2779,7 +2779,8 @@ def to_sql(
         ----------
         name : str
             Name of SQL table.
-        con : sqlalchemy.engine.(Engine or Connection) or sqlite3.Connection
+        con : ADBC connection, sqlalchemy.engine.(Engine or Connection) or sqlite3.Connection
+            ADBC provides high performance I/O with native type support, where available.
             Using SQLAlchemy makes it possible to use any DB supported by that
             library. Legacy support is provided for sqlite3.Connection objects. The user
             is responsible for engine disposal and connection closure for the SQLAlchemy
@@ -2966,6 +2967,22 @@ def to_sql(
         >>> with engine.connect() as conn:
         ...     conn.execute(text("SELECT * FROM integers")).fetchall()
         [(1,), (None,), (2,)]
+
+        .. versionadded:: 2.2.0
+
+           pandas now supports writing via ADBC drivers
+
+        >>> df = pd.DataFrame({'name' : ['User 10', 'User 11', 'User 12']})
+        >>> df
+              name
+        0  User 10
+        1  User 11
+        2  User 12
+
+        >>> from adbc_driver_sqlite import dbapi  # doctest:+SKIP
+        >>> with dbapi.connect("sqlite://") as conn:  # doctest:+SKIP
+        ...     df.to_sql(name="users", con=conn)
+        3
         """  # noqa: E501
         from pandas.io import sql