favor fast_executemany over insertmanyvalues when set
Changed the bulk INSERT strategy used for SQL Server "executemany" with
pyodbc when ``fast_executemany`` is set to ``True`` by using
``fast_executemany`` / ``cursor.executemany()`` for bulk INSERT that does
not include RETURNING, restoring the same behavior as was used in
SQLAlchemy 1.4 when this parameter is set. For INSERT statements that use
RETURNING, the "insertmanyvalues" strategy continues to be used as it is
the only current strategy that supports RETURNING with bulk INSERT.
Previously, SQLAlchemy 2.0 would use "insertmanyvalues" for all INSERT
statements when ``use_insertmanyvalues`` was left at its default of
``False``, ignoring if ``fast_executemany`` was set.
New performance details from end users have shown that ``fast_executemany``
is still much faster for very large datasets as it uses ODBC commands that
can receive all rows in a single round trip, allowing for much larger
datasizes than the batches that can be sent by the current
"insertmanyvalues" strategy.