hungarianhc

Not that locked in - you can just move your vectors to another platform, no?

Vectroid co-founder here. We're huge fans of open source. My co-founder, Talip, made Hazelcast, which is open source.

It might make sense to open source all or part of Vectroid at some point in the future, but at the moment, we feel that would slow us down.

I hate vendor lock-in just as much as the next person. I believe data portability is the ACTUAL counter to vendor lock-in. If we have clean APIs to get your data in, get your data out, and the ability to bulk export your data (which we need to implement soon!), then there's less of a concern, in my opinion.

I also totally understand and respect that some people only want open source software. I'm certainly like that w/ my homelab setup! Except for Plex... Love Plex... Usually.

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.

100GB of data storage doesn't cost us that much money, since we're based on object storage.

You're right that the word "forever" implies outlasting the life of our company. But while we're around and existing, we will not take away the free plan from anyone who has it, and we intend to keep it around for new users.

It's not just that we're raging philanthropists. We want to make money, but our business model is to make money off the larger use-cases, not take $100 / month from people with a credit card.

Hey, we're launching a free tier for our new serverless vector search platform. It's also the fastest cloud based vector search platform. Here are some benchmarks.

- P95 Latency: 38ms with >90% recall on an e-commerce 10M vector dataset (2,688 dimensions) - P95 Latency: 32ms with >95% recall on MS Marco 138M vector dataset (1024 dimensions) - Indexing Speed: 48 minutes on the Deep1B 1B vectors dataset (96 dimensions)

Would love your thoughts. Give it a try. No credit card needed.

Hey. We are releasing Vectroid, a serverless vector search platform. From what we can tell, it's the fastest on the market. But we'd love your help to validate that. We are going to announce a pretty nice "free for life" tier soon. Right now you can log in and try it with no limits at no cost. If you end up using it and you find things we can improve, please let us know. Enjoy!

P.S. no, for now it's not open source. P.P.S. today it's cloud only, but we are working on a full self managed experience that you can install on your own infrastructure.