Don't misunderstand. There are plenty of times when something else is the right choice. I'm just saying, when I have a say in the matter, folks need to clear that bar -- "tell me why tool xyz is going to be so much better than postgres for this use case that it justifies the overhead of adding another piece of software infrastructure."
Like, you want to add a document database? Obviously Mongo, Elasticsearch, etc are "best of breed." But Postgres is pretty capable and we're already good at it. Are we ever going to have so many documents that e.g. Elasticsearch's mostly-effortless horizontal scaling even comes into play? If you don't ever see yourself scaling past 1,000 documents then adding a new piece of infra is a total joke. I see that kind of thing all the time. I can't tell if developers truly do not understand scale, or if they truly do not give a f--- and simply want to play with shiny new toys and enrich their resumes.
This is being repeated so often. And yet — the above is true, IF (and that's a big if for some of us) you are OK with having your database on a single machine.
If you want a distributed database with strict serializability, where some nodes can go down and you still get correct answers, Postgres is not it.
But I've also been burned by people reflexively reaching for $SHINY_NEW_TOY by default, when really there is no need. Architects and senior-level devs are the worst offenders. They throw a bunch of needlessly buzzword-compliant infra at a problem and then move on. They have the time and freedom to learn $SHINY_NEW_TOY well enough to MVP a product, but then the project is passed on to people who don't have that luxury.
I feel like there's a progression that often happens:
1. Early engineers: stick to Postgres or another RDBMS because it's all they know
2. Mid-stage engineers with "senior" in their title for the first time: reach for $SHINY_NEW_TOY
3. Late-stage engineers: stick to Postgres because it's something the whole team already knows and they recognize the true long-term cost of throwing multiple new bits of software infra into the mix
> Mother Postgres can do no wrong.
I'll say that Postgres is usually the answer for the vast majority of use-cases. Even when you think you need something else to do something different, it's probably still a good enough solution. I've seen teams pitching other system just because they wanted to push a bunch of JSON. Guess what, PG can handle that fine and even run SQL queries against that. PG can access other database systems with its foreign data wrappers(https://wiki.postgresql.org/wiki/Foreign_data_wrappers).
The main difficulty is that horizontally scaling it is not trivial(although not impossible, and that can be improved with third party companies).