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Vast majority of cases I've come across, if not all of them, only suffer from any reliance on 90s era RDBMS systems.

And it's never about JSON, it's about latency and resilience, about being able to simply add and replace nodes, about just working in a modern distributed environment.



How many systems actually need a distributed database though? In my experience its usually resume driven development that makes the choice to go NoSQL.


Dear God, this. 90% of the people reading this (or more) - myself included - are currently working on a system that averages fewer than 100 concurrent users. I’ve worked on big systems, and DBs like Cassandra are great, and absolutely have their place, and that place is likely not your system. Quit over complicating everything, please. Please.


I love this comment, because it's exactly how I feel about when people talk about these systems, designed for big scale.


Anybody who needs more availability than an individual instance can provide.


That's all great until you need to perform a join.


RethinkDB handles joins just fine :)


As does couchbase. :-) Personally I like map-reduces.


So does the multi-model database ArangoDB. https://docs.arangodb.com/3.2/AQL/Examples/Join.html

And some NoSQL databases speak SQL as well - without being relational.

I like the JSON support in PostgreSQL a lot. Very easy to deal with unstructured JSON data while still using common attributes in a relational format. But there are more cases that one might think about - as a relational guy - that benefit from graph databases, document stores or optimized time-series databases.




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