Dunno if it's the quality of the posts here, but I find interesting to see that when we talk about SQL nobody complains about it : nobody says there are better alternative, nobody talks about the great schism between the last 2 major revisions of the SQL standard,... (IMHO, SQL is one of the oldest languages and it is still super powerful and used like hell in production environment, but that's just a point of view)
Databases, data interchange formats, and the concepts they represent are mapped out in graphical tools like ER Studio.
The SQL operations you do to load in data from various sources are done in graphical ETL tools like Microsoft SSIS, Talend etc let you draw diagrams which replace SQL. They are more properly a way of programming an engine that runs the SQL but also does things like monitor for incoming files, query webservices etc. Some also provide a technology neutral way to express transforms that can be run in SQL but also on Hadoop or whatever. That said, you sometimes need to go in and write the SQL for optimization.
Enterprise Service Bus sit between multiple databases and multiple data sources and consumers, and the interfaces these provide replace SQL queries. Typically graphical tools or configuration files are used to configure the relationship between the endpoints they provide and databases.
Even outside enterprise land, people rarely write SQL when defining and interfacing with databases. They use an ORM, and a lot of popular ORMs will create a database and provide a way of accessing it so that you never write SQL.
Technologies like OData mean that applications can query data by proxy without needing to know the model it is stored as, and the mapping between the model OData presents and the database is typically implemented using an ORM.
Cloud computing means people with very large databases increasingly want to spread the processing across many slower machines rather than spending the budget on one specialist data processing server with very fast IO. SQL is replaced by other languages in this case (although SQL like languages are making a bit of a comeback).
Finally, in academia and certain very data datacentric industries, SPARQL and successors are still a thing.
I think there is a big divide between enterprise development and what we learn in school / hackernews here. A lot of people outside the industry are not aware of these ecosystems of applications.
I wouldn't recommend any of these over SQL in all cases. They are technologies that solve a problem and you should consider them if you have that problem.