[Mariehane]

I took Ghislain Fourny's Big Data course at ETH last year and found working with JSONiq quite pleasant. I think it makes writing complex queries quite simple, and way more readable than trying to do the same in a query language like SQL, XPath, etc, and since json seems to be fairly standard it is also useable out-of-the-box for a lot of data "in the wild". It is my impression that the tooling is a bit difficult to setup though.

Another thing is that it supposedly can scale to absolutely massive datasets, since there is a Rumbe/Hadoop backend.

[heresie-dabord]

It's interesting to watch solutions and anti-patterns repeat in history ("the time-series of Reality").

Structuring data is an art and a skill. Perhaps not taught very well.

There is a low-cost solution: CSV, TSV, lines of text.

The high-cost solution is relational structure and servers.

In the middle range, with risk of expensive tooling and glaring anti-patterns, are XML and JSON.

The latter can both be used simply or with grotesque opacity. A some point, feeding the monster becomes a main activity of the village. At which point, the villagers elect a new monster with their shovels and pitchforks.

[rendall]

I'm not exactly sure what you're talking about, but I like it / am scared by it

[ocrb]

Was the same for me. Like others here, I was quite sceptical because I use Python / JS on a daily basis as a JSON query language, but after I got used to it, I really liked the language and think that it could increase my productivity if I would use it more often.