Genuinely do not understand the point of these tools. There is already a practically natural language to query RDBMS; it’s called SQL. I guarantee you, anyone who knows any other language could learn enough SQL to do 99% of what they wanted in a couple of hours. Give it a day of intensive study, and you’d know the rest. It’s just not that complicated.

SQL is simple for simple needs, basic joins and some basic aggregates. Even that you won't learn in 2 hours. And that is just scratching the surface of what can be done in SQL and what you need to query. With LLMs and tools like this you simply say what you need in english, you don't need to understand the normalizations, m:n relation tables, CTEs, functions, JSON access operators, etc.

Without having looked at it, I would assume the value comes from not having to know the data model in great detail, such that you can phrase your query using natural language, like

"Give me all the back office account postings for payment transfers of CCP cleared IRD trades which settled yesterday with a payment amount over 1M having a value date in two days"

That's what I'd like to be able to say and get an accurate response.

In a business, a management decision maker has to rely on a Db analyst if any query they have cannot be answered by any front end tool they have been given. And that introduces latency to the process

A 100% accurate ai powered solution would have many customers.

But can this generation of llms produce 100% accuracy?

and yet this was on the front page of hacker news for an entire day :D

it's all about friction. why spend minutes writing a query when you can spend 5 seconds speaking the result you want and get 90-100% of the way there.