diff --git a/pandas/io/sql.py b/pandas/io/sql.py
index d4aab05b22adf..aa4bcd8b1565a 100644
--- a/pandas/io/sql.py
+++ b/pandas/io/sql.py
@@ -7,7 +7,7 @@
 from datetime import date, datetime, time
 from functools import partial
 import re
-from typing import Any, Dict, Iterator, List, Optional, Sequence, Union, overload
+from typing import Any, Dict, Iterator, List, Optional, Sequence, Union, cast, overload
 import warnings
 
 import numpy as np
@@ -383,6 +383,8 @@ def read_sql_query(
         Data type for data or columns. E.g. np.float64 or
         {‘a’: np.float64, ‘b’: np.int32, ‘c’: ‘Int64’}
 
+        .. versionadded:: 1.3.0
+
     Returns
     -------
     DataFrame or Iterator[DataFrame]
@@ -609,7 +611,7 @@ def to_sql(
     index: bool = True,
     index_label=None,
     chunksize: Optional[int] = None,
-    dtype=None,
+    dtype: Optional[DtypeArg] = None,
     method: Optional[str] = None,
 ) -> None:
     """
@@ -768,7 +770,7 @@ def __init__(
         index_label=None,
         schema=None,
         keys=None,
-        dtype=None,
+        dtype: Optional[DtypeArg] = None,
     ):
         self.name = name
         self.pd_sql = pandas_sql_engine
@@ -1108,9 +1110,11 @@ def _harmonize_columns(self, parse_dates=None):
 
     def _sqlalchemy_type(self, col):
 
-        dtype = self.dtype or {}
-        if col.name in dtype:
-            return self.dtype[col.name]
+        dtype: DtypeArg = self.dtype or {}
+        if is_dict_like(dtype):
+            dtype = cast(dict, dtype)
+            if col.name in dtype:
+                return dtype[col.name]
 
         # Infer type of column, while ignoring missing values.
         # Needed for inserting typed data containing NULLs, GH 8778.
@@ -1209,7 +1213,18 @@ def read_sql(self, *args, **kwargs):
             "connectable or sqlite connection"
         )
 
-    def to_sql(self, *args, **kwargs):
+    def to_sql(
+        self,
+        frame,
+        name,
+        if_exists="fail",
+        index=True,
+        index_label=None,
+        schema=None,
+        chunksize=None,
+        dtype: Optional[DtypeArg] = None,
+        method=None,
+    ):
         raise ValueError(
             "PandasSQL must be created with an SQLAlchemy "
             "connectable or sqlite connection"
@@ -1436,7 +1451,7 @@ def to_sql(
         index_label=None,
         schema=None,
         chunksize=None,
-        dtype=None,
+        dtype: Optional[DtypeArg] = None,
         method=None,
     ):
         """
@@ -1480,10 +1495,12 @@ def to_sql(
 
             .. versionadded:: 0.24.0
         """
-        if dtype and not is_dict_like(dtype):
-            dtype = {col_name: dtype for col_name in frame}
+        if dtype:
+            if not is_dict_like(dtype):
+                dtype = {col_name: dtype for col_name in frame}
+            else:
+                dtype = cast(dict, dtype)
 
-        if dtype is not None:
             from sqlalchemy.types import TypeEngine, to_instance
 
             for col, my_type in dtype.items():
@@ -1569,7 +1586,7 @@ def _create_sql_schema(
         frame: DataFrame,
         table_name: str,
         keys: Optional[List[str]] = None,
-        dtype: Optional[dict] = None,
+        dtype: Optional[DtypeArg] = None,
         schema: Optional[str] = None,
     ):
         table = SQLTable(
@@ -1740,9 +1757,11 @@ def _create_table_setup(self):
         return create_stmts
 
     def _sql_type_name(self, col):
-        dtype = self.dtype or {}
-        if col.name in dtype:
-            return dtype[col.name]
+        dtype: DtypeArg = self.dtype or {}
+        if is_dict_like(dtype):
+            dtype = cast(dict, dtype)
+            if col.name in dtype:
+                return dtype[col.name]
 
         # Infer type of column, while ignoring missing values.
         # Needed for inserting typed data containing NULLs, GH 8778.
@@ -1901,7 +1920,7 @@ def to_sql(
         index_label=None,
         schema=None,
         chunksize=None,
-        dtype=None,
+        dtype: Optional[DtypeArg] = None,
         method=None,
     ):
         """
@@ -1944,10 +1963,12 @@ def to_sql(
 
             .. versionadded:: 0.24.0
         """
-        if dtype and not is_dict_like(dtype):
-            dtype = {col_name: dtype for col_name in frame}
+        if dtype:
+            if not is_dict_like(dtype):
+                dtype = {col_name: dtype for col_name in frame}
+            else:
+                dtype = cast(dict, dtype)
 
-        if dtype is not None:
             for col, my_type in dtype.items():
                 if not isinstance(my_type, str):
                     raise ValueError(f"{col} ({my_type}) not a string")
@@ -1986,7 +2007,7 @@ def _create_sql_schema(
         frame,
         table_name: str,
         keys=None,
-        dtype=None,
+        dtype: Optional[DtypeArg] = None,
         schema: Optional[str] = None,
     ):
         table = SQLiteTable(
@@ -2002,7 +2023,12 @@ def _create_sql_schema(
 
 
 def get_schema(
-    frame, name: str, keys=None, con=None, dtype=None, schema: Optional[str] = None
+    frame,
+    name: str,
+    keys=None,
+    con=None,
+    dtype: Optional[DtypeArg] = None,
+    schema: Optional[str] = None,
 ):
     """
     Get the SQL db table schema for the given frame.