diff --git a/pyiceberg/table/__init__.py b/pyiceberg/table/__init__.py
index 8ff299ce6a..62de9a4d2e 100644
--- a/pyiceberg/table/__init__.py
+++ b/pyiceberg/table/__init__.py
@@ -579,7 +579,9 @@ def overwrite(
             self.table_metadata.schema(), provided_schema=df.schema, downcast_ns_timestamp_to_us=downcast_ns_timestamp_to_us
         )
 
-        self.delete(delete_filter=overwrite_filter, case_sensitive=case_sensitive, snapshot_properties=snapshot_properties)
+        if overwrite_filter != AlwaysFalse():
+            # Only delete when the filter is != AlwaysFalse
+            self.delete(delete_filter=overwrite_filter, case_sensitive=case_sensitive, snapshot_properties=snapshot_properties)
 
         with self._append_snapshot_producer(snapshot_properties) as append_files:
             # skip writing data files if the dataframe is empty
diff --git a/pyiceberg/table/upsert_util.py b/pyiceberg/table/upsert_util.py
index c12351d45c..6cbafcd093 100644
--- a/pyiceberg/table/upsert_util.py
+++ b/pyiceberg/table/upsert_util.py
@@ -67,6 +67,10 @@ def get_rows_to_update(source_table: pa.Table, target_table: pa.Table, join_cols
 
     non_key_cols = list(all_columns - join_cols_set)
 
+    if len(target_table) == 0:
+        # When the target table is empty, there is nothing to update :)
+        return source_table.schema.empty_table()
+
     match_expr = functools.reduce(operator.and_, [pc.field(col).isin(target_table.column(col).to_pylist()) for col in join_cols])
 
     matching_source_rows = source_table.filter(match_expr)
diff --git a/tests/table/test_upsert.py b/tests/table/test_upsert.py
index c97015e650..d8e8b8c280 100644
--- a/tests/table/test_upsert.py
+++ b/tests/table/test_upsert.py
@@ -371,6 +371,42 @@ def test_upsert_with_identifier_fields(catalog: Catalog) -> None:
     assert upd.rows_inserted == 1
 
 
+def test_upsert_into_empty_table(catalog: Catalog) -> None:
+    identifier = "default.test_upsert_into_empty_table"
+    _drop_table(catalog, identifier)
+
+    schema = Schema(
+        NestedField(1, "city", StringType(), required=True),
+        NestedField(2, "inhabitants", IntegerType(), required=True),
+        # Mark City as the identifier field, also known as the primary-key
+        identifier_field_ids=[1],
+    )
+
+    tbl = catalog.create_table(identifier, schema=schema)
+
+    arrow_schema = pa.schema(
+        [
+            pa.field("city", pa.string(), nullable=False),
+            pa.field("inhabitants", pa.int32(), nullable=False),
+        ]
+    )
+
+    # Write some data
+    df = pa.Table.from_pylist(
+        [
+            {"city": "Amsterdam", "inhabitants": 921402},
+            {"city": "San Francisco", "inhabitants": 808988},
+            {"city": "Drachten", "inhabitants": 45019},
+            {"city": "Paris", "inhabitants": 2103000},
+        ],
+        schema=arrow_schema,
+    )
+    upd = tbl.upsert(df)
+
+    assert upd.rows_updated == 0
+    assert upd.rows_inserted == 4
+
+
 def test_create_match_filter_single_condition() -> None:
     """
     Test create_match_filter with a composite key where the source yields exactly one unique key.