diff --git a/paimon-spark/paimon-spark-ut/src/test/scala/org/apache/paimon/spark/sql/WriteMergeSchemaTest.scala b/paimon-spark/paimon-spark-ut/src/test/scala/org/apache/paimon/spark/sql/WriteMergeSchemaTest.scala
index de506cc5c298..878d755900b5 100644
--- a/paimon-spark/paimon-spark-ut/src/test/scala/org/apache/paimon/spark/sql/WriteMergeSchemaTest.scala
+++ b/paimon-spark/paimon-spark-ut/src/test/scala/org/apache/paimon/spark/sql/WriteMergeSchemaTest.scala
@@ -100,4 +100,232 @@ class WriteMergeSchemaTest extends PaimonSparkTestBase {
       }
     }
   }
+
+  test("Write merge schema: fail when merge schema is disabled but new columns are provided") {
+    withTable("t") {
+      withSparkSQLConf("spark.paimon.write.merge-schema" -> "false") {
+        sql("CREATE TABLE t (a INT, b STRING)")
+        sql("INSERT INTO t VALUES (1, '1'), (2, '2')")
+
+        val error = intercept[RuntimeException] {
+          spark.sql("INSERT INTO t BY NAME SELECT 3 AS a, '3' AS b, 3 AS c")
+        }.getMessage
+        assert(error.contains("the number of data columns don't match with the table schema's"))
+      }
+    }
+  }
+
+  test("Write merge schema: numeric types") {
+    withTable("t") {
+      withSparkSQLConf("spark.paimon.write.merge-schema" -> "true") {
+        sql("CREATE TABLE t (a INT, b STRING)")
+        sql("INSERT INTO t VALUES (1, '1'), (2, '2')")
+
+        // new columns with numeric types
+        sql(
+          "INSERT INTO t BY NAME SELECT 3 AS a, '3' AS b, " +
+            "cast(10 as byte) AS byte_col, " +
+            "cast(1000 as short) AS short_col, " +
+            "100000 AS int_col, " +
+            "10000000000L AS long_col, " +
+            "cast(1.23 as float) AS float_col, " +
+            "4.56 AS double_col, " +
+            "cast(7.89 as decimal(10,2)) AS decimal_col")
+        checkAnswer(
+          sql("SELECT * FROM t ORDER BY a"),
+          Seq(
+            Row(1, "1", null, null, null, null, null, null, null),
+            Row(2, "2", null, null, null, null, null, null, null),
+            Row(
+              3,
+              "3",
+              10.toByte,
+              1000.toShort,
+              100000,
+              10000000000L,
+              1.23f,
+              4.56d,
+              java.math.BigDecimal.valueOf(7.89))
+          )
+        )
+
+        // missing columns and new columns with numeric types
+        sql(
+          "INSERT INTO t BY NAME SELECT '4' AS d, '4' AS b, " +
+            "cast(20 as byte) AS byte_col, " +
+            "cast(2000 as short) AS short_col, " +
+            "200000 AS int_col, " +
+            "20000000000L AS long_col, " +
+            "cast(2.34 as float) AS float_col, " +
+            "5.67 AS double_col, " +
+            "cast(8.96 as decimal(10,2)) AS decimal_col")
+        checkAnswer(
+          sql("SELECT * FROM t ORDER BY a"),
+          Seq(
+            Row(
+              null,
+              "4",
+              20.toByte,
+              2000.toShort,
+              200000,
+              20000000000L,
+              2.34f,
+              5.67d,
+              java.math.BigDecimal.valueOf(8.96),
+              "4"),
+            Row(1, "1", null, null, null, null, null, null, null, null),
+            Row(2, "2", null, null, null, null, null, null, null, null),
+            Row(
+              3,
+              "3",
+              10.toByte,
+              1000.toShort,
+              100000,
+              10000000000L,
+              1.23f,
+              4.56d,
+              java.math.BigDecimal.valueOf(7.89),
+              null)
+          )
+        )
+      }
+    }
+  }
+
+  test("Write merge schema: date and time types") {
+    withTable("t") {
+      withSparkSQLConf("spark.paimon.write.merge-schema" -> "true") {
+        sql("CREATE TABLE t (a INT, b STRING)")
+        sql("INSERT INTO t VALUES (1, '1'), (2, '2')")
+
+        // new columns with date and time types
+        sql(
+          "INSERT INTO t BY NAME SELECT 3 AS a, '3' AS b, " +
+            "cast('2023-01-01' as date) AS date_col, " +
+            "cast('2023-01-01 12:00:00' as timestamp) AS timestamp_col")
+        checkAnswer(
+          sql("SELECT * FROM t ORDER BY a"),
+          Seq(
+            Row(1, "1", null, null),
+            Row(2, "2", null, null),
+            Row(
+              3,
+              "3",
+              java.sql.Date.valueOf("2023-01-01"),
+              java.sql.Timestamp.valueOf("2023-01-01 12:00:00"))
+          )
+        )
+
+        // missing columns and new columns with date and time types
+        sql(
+          "INSERT INTO t BY NAME SELECT '4' AS d, '4' AS b, " +
+            "cast('2023-12-31' as date) AS date_col, " +
+            "cast('2023-12-31 23:59:59' as timestamp) AS timestamp_col")
+        checkAnswer(
+          sql("SELECT * FROM t ORDER BY a"),
+          Seq(
+            Row(
+              null,
+              "4",
+              java.sql.Date.valueOf("2023-12-31"),
+              java.sql.Timestamp.valueOf("2023-12-31 23:59:59"),
+              "4"),
+            Row(1, "1", null, null, null),
+            Row(2, "2", null, null, null),
+            Row(
+              3,
+              "3",
+              java.sql.Date.valueOf("2023-01-01"),
+              java.sql.Timestamp.valueOf("2023-01-01 12:00:00"),
+              null)
+          )
+        )
+      }
+    }
+  }
+
+  test("Write merge schema: complex types") {
+    withTable("t") {
+      withSparkSQLConf("spark.paimon.write.merge-schema" -> "true") {
+        sql("CREATE TABLE t (a INT, b STRING)")
+        sql("INSERT INTO t VALUES (1, '1'), (2, '2')")
+
+        // new columns with complex types
+        sql(
+          "INSERT INTO t BY NAME SELECT 3 AS a, '3' AS b, " +
+            "array(1, 2, 3) AS array_col, " +
+            "map('key1', 'value1', 'key2', 'value2') AS map_col, " +
+            "struct('x', 1) AS struct_col")
+        checkAnswer(
+          sql("SELECT * FROM t ORDER BY a"),
+          Seq(
+            Row(1, "1", null, null, null),
+            Row(2, "2", null, null, null),
+            Row(3, "3", Array(1, 2, 3), Map("key1" -> "value1", "key2" -> "value2"), Row("x", 1))
+          )
+        )
+
+        // missing columns and new columns with complex types
+        sql(
+          "INSERT INTO t BY NAME SELECT '4' AS d, '4' AS b, " +
+            "array(4, 5, 6) AS array_col, " +
+            "map('key3', 'value3') AS map_col, " +
+            "struct('y', 2) AS struct_col")
+        checkAnswer(
+          sql("SELECT * FROM t ORDER BY a"),
+          Seq(
+            Row(null, "4", Array(4, 5, 6), Map("key3" -> "value3"), Row("y", 2), "4"),
+            Row(1, "1", null, null, null, null),
+            Row(2, "2", null, null, null, null),
+            Row(
+              3,
+              "3",
+              Array(1, 2, 3),
+              Map("key1" -> "value1", "key2" -> "value2"),
+              Row("x", 1),
+              null)
+          )
+        )
+      }
+    }
+  }
+
+  test("Write merge schema: binary and boolean types") {
+    withTable("t") {
+      withSparkSQLConf("spark.paimon.write.merge-schema" -> "true") {
+        sql("CREATE TABLE t (a INT, b STRING)")
+        sql("INSERT INTO t VALUES (1, '1'), (2, '2')")
+
+        // new columns with binary and boolean types
+        sql(
+          "INSERT INTO t BY NAME SELECT 3 AS a, '3' AS b, " +
+            "cast('binary_data' as binary) AS binary_col, " +
+            "true AS boolean_col")
+        checkAnswer(
+          sql("SELECT * FROM t ORDER BY a"),
+          Seq(
+            Row(1, "1", null, null),
+            Row(2, "2", null, null),
+            Row(3, "3", "binary_data".getBytes("UTF-8"), true)
+          )
+        )
+
+        // missing columns and new columns with binary and boolean types
+        sql(
+          "INSERT INTO t BY NAME SELECT '4' AS d, '4' AS b, " +
+            "cast('more_data' as binary) AS binary_col, " +
+            "false AS boolean_col")
+        checkAnswer(
+          sql("SELECT * FROM t ORDER BY a"),
+          Seq(
+            Row(null, "4", "more_data".getBytes("UTF-8"), false, "4"),
+            Row(1, "1", null, null, null),
+            Row(2, "2", null, null, null),
+            Row(3, "3", "binary_data".getBytes("UTF-8"), true, null)
+          )
+        )
+      }
+    }
+  }
+
 }