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> way beyond the capabilities of standard SQL Maybe some examples would help > AI and LLMs (coming soon) Why?
by demaga 2y ago
> way beyond the capabilities of standard SQL
Maybe some examples would help
> AI and LLMs (coming soon)
Why?
- cpimhoff 2y ago> way beyond the capabilities of standard SQL Maybe the more precise language would be "way beyond the _expressive_ capabilities of standard SQL". Ultimately Hashquery compiles into SQL for execution, in that way it's a bit of a transpiler. One concrete example is funnel analysis. In SQL, an efficient funnel analysis on large data sets will span several hundred lines of pipelined queries; writing, reading, and re-parameterizing this is very challenging. In Hashquery, it's abstracted into a single function call: `model.funnel(*str[])`. > AI and LLMs (coming soon) Frankly? SEO just told us to drop "AI" _somewhere_ on the page for new `.dev` website. I agree it's a little silly to make it a top-line bullet point. We do think Hashquery is better suited for coding co-pilot tools, as it's a known language, and you can establish API boundaries that an AI tool won't break into and futz with (good for writing queries on top of already defined business logic).