Point being you can say just about the same thing about any other database. They are all flawed for one reason or another. I happen to like Mongo quite a lot, but I rarely use it. You need to understand what situations it works best in and it's unfair to both it and yourself to generalize and wish it dead.
PostgreSQL is eating Oracle's customers little by little.
RDBMS aren't flawed at all, this is technology that has been perfected for the last 40 years. What is flawed is to think that relational data can be easily stored on a document store (typical mistake).
I think document stores are a great thing; the only problem is that MongoDB isn't a good document store.
To add to that - you know when you need one. If you don't know you need a document store, you don't need it.
When you try a good document store, like Solr, you realize how appallingly limited Mongo really is. It's not suited for any practical use outside of demo apps.
If you actually tried using it as one you would realise how ignorant your comment is. Both the Solr and ElasticSearch have gone on record before stating that it should never be used as the source of truth.
I'm working on overhauling (rewriting, from scratch) a project right now where the previous developer decided in his infinite wisdom that using ES as a database was a good idea.
I have tried repeatedly to explain to him, and the product owner, why using a search engine as a storage database is a horrific idea. Owner gets it, dev doesn't. I asked that dev if he could overhaul the project, what would he do, and he said "not use SQL at all, and use ES 100%". <_<
I think this is the problem with Mongo too... you have people misusing it, and then want to throw the baby out with the bath water and act like Mongo is the problem, when really, the problem is how they are using it.
There's no need for the vitriol.
I always hear this, but with no "such as" examples given. Could you please provide some?
Sure, there's PostGIS, but saving a GeoJSON multiline which I can slap an index on works for me.
I have grown fond of Mongo because I've been using it for almost 5 years now. I know its limitations, and also what I can do in RDBMS that I can also do in it.
I sometimes build OLAP logical models at work for clients, and most of what I touch at work is SQL, but sometimes when I start a project I use Mongo instead of SQL.
It's only one use-case, but I hope it is something.
In a standard RDBMS I would probably have a custom datatype for LatLon (or MGRS):
create custom type LatLon(...)
create table Person(id as int, name as string, location as LatLon)
create table Shop(id as int, name as string, location as LatLon)
Find everyone 10k around Macy's:
select p.* from Person p inner join Shop s where s.name="Macy's" and with_distance(p.location, s.location, 10km)