Earlier quoted context omitted.
I used to be a Business Intelligence consultant for enterprises. We built reports, data warehouses, dashboards, etc. From my experience, the article is spot on, not linkbait. Maybe MongoDB is better once you have a well defined query that you need, but I think the point of the parent comment is that those examples of queries are ad-hoc. NoSQL is not as good as SQL when it comes to report specs that are constantly in…
Both of those queries are very easy to perform in MongoDB. For examples of how to easily model and query trees (CONNECT BY PRIOR in SQL) see: http://www.mongodb.org/display/DOCS/Trees+in+MongoDB SUM(CASE IF col IN ('a','b','c') THEN 1 ELSE 0) can be implemented as a group or mapreduce query. I would say that you have a lot more power and flexibility in MongoDB compared to an average SQL database when it comes to ad-h…
The way I read your link it sounds like I need to store the data in a particular way in order to run a parent/child query. That is great if I know that I need that query at design time. What happens if I have tens of millions of records and need to run that report on an ad-hoc basis? Where the relationship may or may not be important?
What if I want to sum the "cost of goods sold" one day and the "items per transaction" the next? Does that not require someone to write code more complex than SQL? Because on Oracle a business analyst can open up Toad and run that query.
If I am wrong then it very well may be that the problem is one of the enterprise not being aware.