diff --git a/py-polars/polars/io/database.py b/py-polars/polars/io/database.py
index 5bae271947fd..76db913aeb02 100644
--- a/py-polars/polars/io/database.py
+++ b/py-polars/polars/io/database.py
@@ -280,23 +280,29 @@ def _from_rows(
 
         if hasattr(self.result, "fetchall"):
             if self.driver_name == "sqlalchemy":
-                column_names = (
-                    list(self.result._metadata.keys)
-                    if hasattr(self.result, "_metadata")
-                    else [desc[0] for desc in self.result.cursor.description]
-                )
+                if hasattr(self.result, "cursor"):
+                    cursor_desc = {d[0]: d[1] for d in self.result.cursor.description}
+                elif hasattr(self.result, "_metadata"):
+                    cursor_desc = {k: None for k in self.result._metadata.keys}
+                else:
+                    msg = f"Unable to determine metadata from query result; {self.result!r}"
+                    raise ValueError(msg)
             else:
-                column_names = [desc[0] for desc in self.result.description]
+                cursor_desc = {d[0]: d[1] for d in self.result.description}
+
+            # TODO: refine types based on the cursor description's type_code,
+            #  if/where available? (for now, we just read the column names)
+            result_columns = list(cursor_desc)
 
             frames = (
                 DataFrame(
                     data=rows,
-                    schema=column_names,
+                    schema=result_columns,
                     schema_overrides=schema_overrides,
                     orient="row",
                 )
                 for rows in (
-                    self._fetchmany_rows(self.result, batch_size)
+                    list(self._fetchmany_rows(self.result, batch_size))
                     if iter_batches
                     else [self._fetchall_rows(self.result)]  # type: ignore[list-item]
                 )
@@ -458,9 +464,10 @@ def read_database(  # noqa: D417
         be a suitable "Selectable", otherwise it is expected to be a string).
     connection
         An instantiated connection (or cursor/client object) that the query can be
-        executed against. Can also pass a valid ODBC connection string, starting with
-        "Driver=", in which case the `arrow-odbc` package will be used to establish
-        the connection and return Arrow-native data to Polars.
+        executed against. Can also pass a valid ODBC connection string, identified as
+        such if it contains the string "Driver=", in which case the `arrow-odbc`
+        package will be used to establish the connection and return Arrow-native data
+        to Polars.
     iter_batches
         Return an iterator of DataFrames, where each DataFrame represents a batch of
         data returned by the query; this can be useful for processing large resultsets
@@ -560,7 +567,7 @@ def read_database(  # noqa: D417
     """  # noqa: W505
     if isinstance(connection, str):
         # check for odbc connection string
-        if re.sub(r"\s", "", connection[:20]).lower().startswith("driver="):
+        if re.search(r"\bdriver\s*=\s*{[^}]+?}", connection, re.IGNORECASE):
             try:
                 import arrow_odbc  # noqa: F401
             except ModuleNotFoundError: