The underlying C library interacts directly with the postgres query parser (therefore, Postgres source). So unless you rewrite postgres in Rust, you wouldn't be able to do that.
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Grug says bad.
In all seriousness, the rough argument is that it's a "big brain" way of thinking. It sounds great on paper, but is often times not the easiest machinery to have to manage when there are simpler options (e.g. just add a method).
It's not bad if you need something quick. I haven't had a large need of ANN in duckdb since it's doing more analytical/exploratory needs, but it's definitely there if you need it.
Just curious what the state of the art around filtered vector search results is? I took a quick look at the SPFresh paper and didn't see it specifically address filtering.
In any API service, it's better to handle via dependency injection IMO.
Instantiate all of your metadata once, and then send that logger down, so that anybody who uses that logger is guaranteed to have the right metadata... the time to add logging is not when you are debugging.
Might be missing my argument here - I stated that there are workable solutions to this like you have pointed out.
But ANN search is still a sledgehammer and building out hybrid solutions that help bridge the gap between this and traditional data stores still have room for innovation.
I don't disagree that rock solid is a good choice, but there is a ton of innovation necessary for data stores.
Especially in the context of embedding search, which this article is also trying to do. We need database that can efficiently store/query high-dimensional embeddings, and handle the nuance of real-world applications as well such as filtered-ANN. There is a ton of innovation in this space and it's crucial to powering the next generation architectures of just about every company out there. At this point, data-stores are becoming a bottleneck for serving embedding search and I cannot understate that advancements in this are extremely important for enabling these solutions. This is why there is an explosion of vector-databases right now.
This article is a great example of where the actual data-providers are not providing the solutions companies need right now, and there is so much room for improvement in this space.
For platform stuff that has speed and correctness as the highest priority? Absolutely. Things like http proxies, message queues, shared infrastructure makes sense to be done in Rust.
For writing a normal networked http/rpc/event stream service Go is probably more than good enough. It’s not a winner-take-all market.
A great example imo is Buoyant’s Linkerd. Rust dataplane proxy as well as a control plane written in Go. Two different requirements for each of those services drove the language requirements
Yes, that means no phone, no headphones, just you and your brain enjoying a walk. Let your mind wonder and be free.