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This is so true.

The problem I have though is that looking around for jobs recently, people want "experience in MongoDB", rather than "ability to recognize when MongoDB is clearly not the best tool for the job".

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I've often wondered why people don't use databases and SQL for more often data analysis. SQL is relatively easy to learn, and there is so much you can do, especially if you use analytical functions. I almost always load the data into a DB, and do as much as I can with straight SQL. And, if I can't do it in SQL, I write a query to the transform the data to the format I need, and then access it via python to do the rest.

They do. In real companies (those with you know, revenue) millions of ordinary people called business analysts, accountants, statisticians use SQL or tools like Business Objects to do real work on multi-terabyte databases called Data Warehouses every day. Have done for years before the first hipster called himself a "data scientist".

There's more you can do with straight SQL than you'd think. Say, multiplication of sparse matrices.

You could always take some Art of War inspiration and learn MongoDB really well before your interview, then once you get in there become the in-house Mongo go-to expert, then use your clout to recommend a replacement. :)

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