So, what does that mean for us? I am shellshocked. I expect prices to increase (good for us). What else should we expect?
They merged partially because they were both being cannibalized by services revenue they couldn't get rid of. Now they are struggling to move to the cloud (see Atlas now)
I'm not sure yet another hadoop distro with a bunch of 1 off tooling that is supposedly faster is the answer. Why is all that stuff even needed?
Dl4j itself has a decent sized user base. Ranging likely from your phone maker to your bank and retail store.
We have our own software distro too which is why I'm commenting on this. We don't try to boil the ocean with a bunch of tech though.
There's a whole new crop of companies focusing on solving bits of the ML problem well rather than trying to do storage and god knows what else.
My point here about you guys is you're trying to compete in what is largely a commodity market. People don't need all this stuff. Simplicity won here. It's not about better tech.
You guys have the same pitch MapR does and largely the same problem: Better tech is only part of the problem with adoption. You need customers, users, and a clear business model when going to market.
Cloudera and Horton ran one playbook that at least somewhat worked (it got them public) and now they can focus on competing with the cloud vendors, which made the right decision and just made commonly used software easy to use.
Your pitch is still about differentiated tech, not a large install base, a differentiated business model
and something related to people like a good partner ecosystem.
Your pitch here requires tons of services.
People don't know how to use all of this stuff especially on prem.
It takes more than just code to build a business.
I say this as someone who's been doing this since 2013. It's not easy.
If you want to train DNNs on a hundred GPUs today on-premise on TensorFlow, come to us, we can do it. They can't.
the same point. Tech doesn't matter. Simplicity does.
Even in our own product line, we only do a small
subset of this. We don't even require a cluster
to run. We also work with tech that people use.
You are currently competing with horovod
and kubeflow. eg: "competing with free"
You need more than that to survive.
Generally, that comes down to services.
Reference: https://www.logicalclocks.com/millions-and-millions-of-files...
We have also redesigned the stack around our distributed metadata layer.
We are primarily targeting on-prem right now, but HopsFS would be the fastest DFS in the cloud if you ran it there today.
Do you support Kubernetes too?