quantike

This is cool! Visibility into streams is one of the developer papercuts that my team struggles with, specifically on NATS JetStream which doesn't have a schema registry.

I am working on a similar use-case by creating a DuckDB extension that can stream from NATS JetsStream: https://github.com/quantike/duckstream

Still early days on feature support, but querying with SQL in DuckDB is the path I've been going.

I will need to give this a try.

Incredible tool, definitely going to get a working poc for this with my team. Curious how this can apply across many databases, say in a cluster, checking for discrepancies etc. Wondering if that is a supported feature?

Nice work, really happy to have found this today.

https://quantike.xyz Hoping to be blogging more this year :)

Just this past week I spoke with a local hackathon team who was working on giving consumers access to fair medical pricing by having users ask an LLM about their procedure, which would then cross reference with a pricing database. Simple idea but useful given the variance in procedure costs depending on provider/hospital.

Looks like a cool extension thought I'd love some more detail on why someone would use note codes? What do you use them for?

Nice post. I think about time... all the time haha. There's another source you might enjoy (Re: your NTP and synchronization question) from TigerBeetle: [Implementing Time](https://www.youtube.com/watch?v=QtNmGqWe73g)

I appreciate the reply! Yeah that sounds like the correct path forward is swapping out the type for some enum of numeric types you want to cover.

I'd be curious if there's some benefit to the runtime-memory utilization to baking in the precision of the vector if it's known at comptime/runtime. In my own usage of vector DBs I've only ever used a single-precision (f32), and often have a single, known dimension. But if Helix is aiming for something more general purpose, then it makes sense to offer the mixing of precision and dimension in the internals.

Cheers

I spent a bit of time reading up on the internals and had a question about a small design choice (I am new to DB internals, specifically as they relate to vector DBs).

I notice that in your core vector type (`HVector`), you choose to store the vector data as a `Vec<f64>`. Given what I have seen from most embedding endpoints, they return `f32`s. Is there a particular reason for picking `f64` vs `f32` here? Is the additional precision a way to avoid headaches down the line or is it something I am missing context for?

Really cool project, gonna keep reading the code.

One other point of annoyance with the new UI is that the videos actually aren't aligned vertically.

I really dislike auto-play so I have always strategically rested my cursor in between the columns of video. Now, as I scroll, my cursor will end up within a column that is misaligned and start autoplay. The worst!