noobiemcfoob

The only feature keeping me on Chrome is web bluetooth.

You'll have dumped it into a strict database, giving yourself a false sense of order and organization. But later when you need to query that amorphous data, you might be able to use OPENJSON or something else, but a NoSQL solution will have been built to handle this type of query specifically with utilities like key exists and better handling for keys missing or only sometimes being present.

Then argue honestly and work to steelman other's arguments. To address your point, I'd hardly consider IoT platforms to be a "narrow" usecase. Smaller than the whole of computing, surely, but it's a growing field. The reality is that more and more devices will become available that generate all sorts of hard to predict data. Being able to handle those easily will be a large strength for platforms going forward. Dropping this hard to predict data as JSON into a RDMS will certainly come back to haunt you in 5 years.

What's wrong is that you asked for any usecase and then critique one because it's not broad enough for you.

It's hyperbole. A lot like systems that require hard type declarations for each and every function. The advantage of type systems is performance. Any correctness guarantees that come along with it are nice sugar but hardly the point and often misleading.

I've built IoT platforms where data from any device must be accepted. This is largely where my preference for NoSQL comes from. A device created tomorrow will not have a schema I can predict or control. NoSQL allows the easy integration of that device while a traditional database will at worst require a migration for each new device you want to support.

>use Elasticsearch

Found your problem.

“Why didn’t we use an RDBMS in the first place? “

Because initial application specifications are sparse and definitely wrong. If your application is still up and running 5 years later and your data definition hasn't changed much in the past 3, then maybe refactor around an RDBMS. Designing around rigid structures during your first pass is costly. This is why there's been a rise in NoSQL and dynamic languages.

But as soon as you're using "Maybe", you're impeding much of a type systems strengths, as the article outlined.

It's better to assume all code could throw an error. No statement is safe. This becomes particularly important in distributed computing as resources may be offline at any given moment. It's from this perspective that type systems afford a false sense of security and appear to be scratching the itches of overactive Type As.

It throws an error. Errors are a type of behavior. Some of those error behaviors you can cope with. You catch those. Others you can't. You raise those and either the system can cope or it can't and you crash. What part is nonsensical?

I like the concept of encoding properties, like a boolean of non-empty, in an object.

Beyond that, this article further convinced me type systems are for the pedantic. A given function signature is impossible? Seems like just another strength of a dynamic language.

It was both language and database theory, all focused on Oracle. IIRC, it was titled "Database Administration", but I remember having to draw out schema diagrams and learn all the particular arrow types (one-to-one, one-to-many, etc) and what different block shapes meant in the diagram. All that only to get into industry 5 years later and find no one goes beyond basic squares and maybe double-ended arrows in practice >.>

A Data Analyst is a Data Scientist who can't prove Bayes Theorem.