Some objects are not picklable (see Pickling unpicklable objects). I've had the same issue with Redis connections which seem similar to this, though I'm not sure.

The general advice is to extract the data you need and only pickle that, rather than the connection itself.

Multiprocessing relies on pickling to communicate objects between processes. The pyodbc connection and cursor objects can not be pickled.

>>> cPickle.dumps(aCursor)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/lib64/python2.5/copy_reg.py", line 69, in _reduce_ex
    raise TypeError, "can't pickle %s objects" % base.__name__
TypeError: can't pickle Cursor objects
>>> cPickle.dumps(dbHandle)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/lib64/python2.5/copy_reg.py", line 69, in _reduce_ex
    raise TypeError, "can't pickle %s objects" % base.__name__
TypeError: can't pickle Connection objects

"It puts items in the work_queue", what items? Is it possible the cursor object is getting passed as well?

I was able to recreate the issue using pypyodbc, while the same code seems to work fine with pyodbc. One possible workaround for pypyodbc might be to convert the results to a list of dictionary objects and then serialize that:

import pickle, pypyodbc
connection_string = (
    r"Driver={SQL Server Native Client 10.0};"
    r"Server=(local)\SQLEXPRESS;"
    r"Database=myDb;"
    r"Trusted_connection=yes;"
)
connection = pypyodbc.connect(connection_string)
cur = connection.cursor()
cur.execute("SELECT * FROM Donors")

column_names = [x[0] for x in cur.description]
query_list = [dict(zip(column_names, row)) for row in cur.fetchall()]

with open(r'C:\Users\Gord\Desktop\query_result', 'wb') as f:
    pickle.dump(query_list, f)
cur.close()
connection.close()

So you have a binary file containing a pickled object. A hex dump of the file looks like this:

00000000: 8004 9515 0000 0000 0000 007d 9428 8c03  ...........}.(..
00000010: 666f 6f94 4b01 8c03 6261 7294 4b02 752e  foo.K...bar.K.u.

You can save the object to a binary column, then read it back and unpickle it via pickle.loads like so:

import pyodbc
import pickle

conn_str = (
    r'DRIVER=ODBC Driver 17 for SQL Server;'
    r'SERVER=.\SQLEXPRESS;'
    r'DATABASE=myDb;'
    r'Trusted_Connection=yes;'
)
cnxn = pyodbc.connect(conn_str, autocommit=True)
crsr = cnxn.cursor()
crsr.execute("CREATE TABLE #test (id INT PRIMARY KEY, pkl VARBINARY(max))")

# read pre-pickled object from file and save to table
with open(r'C:\Users\Gord\Desktop\data.pickle', 'rb') as f:
    sql = "INSERT INTO #test (id, pkl) VALUES (?, ?)"
    params = (1, f.read())
    crsr.execute(sql, params)

# read it back from database and unpickle it
pickled_data = crsr.execute("SELECT pkl FROM #test WHERE id=1").fetchval()
unpickled_object = pickle.loads(pickled_data)

print(unpickled_object)
# {'foo': 1, 'bar': 2}

Here is what ended up working (thanks to @Gord Thompson for getting me going in the right direction):

1. Using escaped parametrization -- according to pyodbc standard -- rather than Python's .format(). We ended up changing the query to something like:

q = "UPDATE table \
    SET serializedModel = CONVERT(VARBINARY(MAX), ?) \
    WHERE IDa = CONVERT(uniqueidentifier, ?) AND \
            IDb = CONVERT(uniqueidentifier, ?) AND \
            IDc = CONVERT(uniqueidentifier, ?)"

args = (RF_serialized,
        "x",
        "y",
        "z")

cursor.execute(q, args)
cnxn.commit()

2. Using CONVERT(uniqueidentifier, ?) rather than trying to put in special characters for strings (e.g. \') because SQL Server treats GUIDs/unique identifiers as a datatype.
3. I had a couple of extra queries hanging around from running tests/troubleshooting and I think an extra .execute() on one of them -- that totally messed with the query I was actually trying to fix.