From the second link, summary:

Summary - PostgreSQL ● PostgreSQL has poor performance out of the box ○ Requires a decent amount of tuning to get good performance out of it ● Does not scale well with large number of connections ○ pgBouncer is a must ● Combines ACID compliance with schemaless JSON ● Queries not really intuitive

Summary - MongoDB ● MongoDB has decent performance out of the box. ● Unstable throughput and latency ● Scale well with large number of connections ● Strong horizontal scalability ● Throughput bug is annoying ● MongoDB rolling upgrades are ridiculously easy ● Developer friendly - easy to use!

> PostgreSQL has poor performance out of the box

This is actually a valid point. They should start distributing typical configs for typical AWS-alike machines, current default config is for some underpowered machine from 90s..

> Queries not really intuitive

ISHYGDDT

I would argue that MongoDB queries aren't intuitive but I've known SQL for at least 10 years

For MongoDB in Python I once had to construct a list of two dictionaries containing dictionaries themselves with various two and three character magical key and value names (eg. $gt) in order to query a collection by date. If that's intuitive I'd hate to use something unintuitive.

Oh and MongoDB Compass is a dumpster fire. Query takes too long? Too bad it will time out with no option to let it complete. Also I get to write my query in JSON in compass then I have to convert that to native Python objects if I want to use it from there. With SQL I copy my query from datagrip, inject my parameters and call it a day.

I forgot the best bit, if your query has a subtitle mistake most often you simply get no records back where a similar mistake in SQL throws a helpful exception.

really? best of luck with that. single node, and no faiures - and it still messed its pants: http://jepsen.io/analyses/postgresql-12.3