jeungsp

Nothing fundamentally stops a postgres implementation being equally performant as something like Qdrant.

Fundamentally, an index’s performance is based on the hardware and the algorithm and the quality of implementation. Any optimizations Qdrant can make, we can also make.

We will be benchmarking ourselves against all of the other standalone database options as well and we’ll be working to try and outperform them. Excited to share those once we have them.

We are curious – what are you most concerned about? SELECT time? INDEX size? Latency? Throughput?

We’re built on top of Usearch, which will very soon support sparse vectors. We’re working with them to make sure it also works in Lantern.

Can you tell me more about your use case?

This is a great idea. We will have lots of content in the days ahead to talk about why people should make the switch.

Do you use pgvector now? Would love to switch you over.

Hi, Jeung here, one of the co-founders of Lantern.

You’re right. Our performance is just a bit faster today.

We expect everyone’s performance to continue to improve, but we have lots of improvements coming soon, and we plan to continue to widen the lead.

But there are more important reasons to use Lantern besides performance. If you look at our features list and what’s coming soon, we are looking to create tools that make for better applications and better developer experience.