- Domino makes it really easy to start and manage multiple runs in parallel (think a modern, easy-to-use cluster). If you're doing all this directly with AWS, you're quickly running into pain points managing all your instances and images.
- Domino auto automatically keeps a revisioned history of your work. It supports large files like data sets (which git can't handle) and it tracks the results/artifacts of your analysis (which makes it more like git + CI). These things are critical to analytics workflows, rather than pure software development.
- Domino lets you deploy your analyses as self-service web UI tools, or deploy them to API endpoints. Doing this on your own would involve building an entire web stack around your analysis.
- Domino hosts your analysis centrally so you can share and collaborate with others (yes, this is like github, but on a platform that has all the benefits above).
- The entire product can be installed on-premise, so companies can use the functionality described above without going to the cloud if they don't want to.
Finally, even for pure infrastructure management, we've found that many data scientists don't want to spend their time dealing with system administration. It's true that it's not that hard to start an EC2 instance. But pretty quickly you're installing packages (perhaps in an environment you aren't used to), dealing with security groups, file transfer (configuring S3), etc. People use Domino for the same reason they use Heroku: yes, you could deal with all that, but it might be a better use of your time to let someone else do it.