I dunno that SQL is exactly easy, though. It's one thing to say "select statements are essentially identical to Python list comprehensions", but in practice I still have to look up the Venn diagram chart every time I need to join anything, and performance optimization is still a dark art. I'd say SQL is easy in the same way that Git is easy: you can get away with using just 5% of it, but you'll still need to consult an expert to sort things out when things go sideways.

You could solve that by altogether dropping the Venn diagram metaphor when reasoning about joins. This is the number one problem I see with junior devs who have a hard time grokking SQL. If you think about a join as a cartesian product with a filter, where the type of join defines the type of filter, the reasoning is extremely easy.

Here's a good article about that: https://blog.jooq.org/2016/07/05/say-no-to-venn-diagrams-whe...

The hard parts of "SQL" are the hard parts of data. Joins aren't easier in Mongo. The performance optimizations you reference are tuning of a relational database, not SQL itself.

If you want to work with databases a domain specific language like SQL really provides a lot of value in solving these hard data problems.

> performance optimization is still a dark art

The idea is, in relational databases, that the vast majority of the time you shouldn't have to do it. Because you're writing your queries in a higher level (nay, functional) language, the query planner can understand a lot more about what you're trying to do and actually choose algorithms and implementations that are appropriate for the shape and size of your data. And in 6 months time when your tables are ten times the size, it is able to automatically make new decisions.

More explicit forms of expressing queries have no hope of being able to do this and any performance optimization you do is appropriate only for now and this current dataset.

> I'd say SQL is easy in the same way that Git is easy: you can get away with using just 5% of it, but you'll still need to consult an expert to sort things out when things go sideways.

Mongo and Javascript don't solve that either. In fact you get additional problems by virtue of not being able to do a variety of joins. For extra points, you're going to need to go well beyond javascript with mongo if you want performance. 10gen invented this whole "aggregation framework" to sidestep the performance penalty that javascript brings to the table.

On the other side, the postgresql documentation is second to none. SQL isn't necessarily easy but the postgres documentation gives you an excellent starting point.

Here is the dirty secret of Mongo: you always have a schema, you just don’t have any tools for validating it or enforcing it or manipulating it.