First of all, AWS SageMaker is really a ML system that happens to include Jupyter notebooks as a component. But if you are talking about just the Jupyter notebook part, then I would say - you could use JupyterHub to build your own implementation of SageMaker (you would want to use kubespawner and some deployment of kubernetes if you wanted to scale to multiple nodes). For example, I run https://www.saturncloud.io/, and we orchestrate JupyterHub to do just that.

JupyterHub is more flexible - for example, you could deploy JupyterHub to one beefy server and have Jupyter deployed for many users, which could all read data from a shared filesystem. that kind of thing is not easy to do with SageMaker since everything runs on a separate ec2 instance.

I can't comment on EMR notebooks.