NoSQL are super easy to start with. Then you have a pile of heaping unstructured data that's hard to query, hard to report and gain insight on.
Every data task becomes a programming problem which needs a team to work on to get something that might be stale. With SQL there's a lot of work. But you have a DB that everyone knows. 3rd party tools work. Developer on-boarding is easy. Your boss asks you how many users used feature X in the past month you can actually tell him right away...
Performance is actually good and consistent. Your data is also consistent and respects acid principles. The whole write performance of NoSQL DBs is a bit of a crock that doesn't stand the test of scaling. With proper cashing SQL is as performant when done right and the profiling tools are better. Screw no-SQL. They are just Object Oriented DBs (which were a disaster in the 90s) in new clothes.
Every data task becomes a programming problem which needs a team to work on to get something that might be stale. With SQL there's a lot of work. But you have a DB that everyone knows. 3rd party tools work. Developer on-boarding is easy. Your boss asks you how many users used feature X in the past month you can actually tell him right away...
Performance is actually good and consistent. Your data is also consistent and respects acid principles. The whole write performance of NoSQL DBs is a bit of a crock that doesn't stand the test of scaling. With proper cashing SQL is as performant when done right and the profiling tools are better. Screw no-SQL. They are just Object Oriented DBs (which were a disaster in the 90s) in new clothes.