Comment by hungarianhc

Hey! It's a great question. Co-founder of Vectroid here.

Today, the differences are going to be performance, price, accuracy, flexibility, and some intangible UI elegance.

Performance: We actually INITIALLY built Vectroid for the use-case of billions of vectors and near single digit millisecond latency. During the process of building and talking to users, we found that there are just not that many use-cases (yet!) that are at that scale and require that latency. We still believe the market will get there, but it's not there today. So we re-focused on building a general purpose vector search platform, but we stayed close to our high performance roots, and we're seeing better query performance than the other serverless, object storage backed vector DBs. We think we can get way faster too.

Price: We optimized the heck out of this thing with object storage, pre-emptible virtual machines, etc. We've driven our cost down, and we're passing this to the user, starting with a free tier of 100GB. Actual pricing beyond that coming soon.

Accuracy: With our initial testing, we see recall greater or equal to competitors out there, all while being faster.

Flexibility: We are going to have a self managed version for users who want to run on their own infra, but admittedly, we don't have that today. Still working on it.

Other Product Elegance: My co-founder, Talip, made Hazelcast, and I've always been impressed by how easy it is to use and how the end to end experience is so elegant. As we continue to develop Vectroid, that same level of polish and focus on the UX will be there. As an example, one neat thing we rolled out is direct import of data from Hugging Face. We have lots of other cool ideas.

Apologies for the long winded answer. Feel free to ping us with any additional questions.