>Interesting page : http://www.mongovue.com/2010/11/03/yet-another-mongodb-map-reduce-tutorial/
>
>According to the writer SQL execution was 100 secs; Mongo : 6.
>
>Wondering if this is a fair comparison - i.e. is the T-SQL used improvable ?

Viv, first, SQL vs Mongo/MapReduce is definitely "apples and oranges". Actually more like apples and rice.

Second, this author acknowledged no indexes were used in the SQL example.

Third, a very subtle point here - which RDBMS was the author using for the SQL test? It's MySQL. Hardly a great choice for large data. That leads to the next point:

Fourth, if we do a product implementation vs product implementation, the product implementing SQL would get to use any native functions to further optimize. In the case of SQL Server, it has had geospatial data types and geospatial logic baked into the product since SQL 2008. That would dramatically change the SQL example.

Finally - that suggestion at the end...." For example, you could open cursors in SQL and iterate through all the records in nested for loops"....this smacks of someone who doesn't understand a topic beyond the basics. Sorry, but I call 'em as I see 'em. :)

You don't compare an interpreted language to a product. Don't get me wrong - MapReduce has established a presence. But the premise of the comparison is faulty.

Thanks for the link - it's a good example of one of the many things that can be done in the Big Data realm. Also a good exercise in how to set up a straw man.