Skip to content

Comment on Show HN: NNext.net – A Firebase-like managed vector storage for ML applications

Comments

How's this different from Milvus?

Main thing is that NNext is fully managed - you don’t have to worry about provisioning servers, version upgrades and package installation/ dependencies. One of the main thing I’ve observed about ML engineers is that they typically don’t want to be encumbered by general software engineering / dev-ops tasks like platform management. They want to focus on data.

My 2c opinion: this might have been true pre-k8s. With k8s, it's become a cinch for anyone to run a scalable system in the cloud. I think you need something more differentiated.

Minor sticking point, I want to object to the prefix "with k8s, it's become a cinch...". In my experience, this prefix is only true when followed by phrases such as "shoot yourself in the foot", "over complicate your infrastructure", &c. ;)

provisioning servers, version upgrades and package installation/ dependencies

If that is nnext's only or main value prop, it will have to be changed.

Entire companies are built upon providing fast, managed services - Algolia, Firebase and Heroku to name but a few.

Is your point that the market is simply too small/doesn’t exist or that the value prop is simply too weak / defensible?

Not arguing over managed services, although, they are nearly a yaml file away from being made obsolete.

If there is an OSS system that does everything you do, that isn't a big differentiator. As soon as you have any sort of traction, then the second competitor will swoop in, Lyft, Gitlab, Indiegogo.

You need to have defensible differentiation. Otherwise why not just run the OSS system on K8S and sell the service?

AboutSource Built by g1lg1l

Hackerly is an independent reader for Hacker News, built on the public HN API. Not affiliated with Y Combinator.