MS SQL Server/ODBC package for Python

[Peter Herndon]

:) Knock away, as my info isn't scientific anyway.  In my case, ASA is
*not* local.  The db is running on a 500MHz x 2 server with 768MB RAM,
over 100BaseT connection.  That same server is also running the MSSQL
instance, and IIS.

Running your benchmark, I ran into a couple of interesting points.
Using mx.ODBC, my times were 0.54 seconds and 6.56 seconds
respectively, while using adodbapi my results are 3.55 seconds and 25.9
seconds respectively.  mx.ODBC is faster with the simple query you
provide.

Next I modified the benchmark to reflect my particular circumstances
more accurately (?Maybe?  Comments invited).  I changed the query to
one of the queries in regular use in my application.  This query
selects 26 columns from 3 joined tables, with a where clause "where
f476 = ?", and I provide the missing value as a tuple in the execute
statement.  Note that, as I mentioned in my reply to M-A, the f476
field is not indexed, and is a long varchar.  Again, the system is
bought, so I have no control over the schema. ;)

The other change I made was to reduce the number of iterations from 100
to 10.  Since there are 128000 records in the main table, the wait for
100 iterations was too long for my patience.  Under these
circumstances, mx.ODBC's numbers are 188.49 seconds and 377.56 seconds
respectively, and adodbapi's times are 111.15 seconds and 223.55
seconds respectively.

My first wall-clock impressions are obvious exaggerations of reality,
for which I duly apologize to all.  However, adodbapi did prove to be
faster in my admittedly very wacky common use case.  Slower to connect,
but faster to run a substantial query.

Comments?  Questions?  Suggestions for improvement?