How does this get the maps of the data flows and so on? Does it require read credentials to each data silo, or is there a manual mapping process?

It depends on your ecosystem. If everything lives under one vendor their native catalog will probably work really well for you. But most of the time (especially for older orgs) there's usually a huge fragmented ecosystem of data assets that aren't easily discoverable and spread across multiple teams and vendors.

I like to think of Marmot as more of "operational" catalog with more of a focus on usability for individual contributors and not just data engineers. The key focus being on simplicity, in terms of both deployments and usability.

Amundsen has two databases and three services in its architecture diagram. For me, that's a smell that you now have risk of inconsistency between the two, and you may have to learn how to tune elasticsearch and Neo4j...

Versus the conceptually simpler "one binary, one container, one storage volume/database" model.

I acknowledge it's a false choice and a semi-silly thing to fixate on (how do you perf-tune ingestion queue problems vs write problems vs read problems for a go binary?)..

But, like, I have 10 different systems I'm already debugging.

Adding another one like a data catalog that is supposed to make life easier and discovering I now have 5-subsystems-in-a-trenchcoat to possibly need to debug means I'm spending even more time on babysitting the metadata manager rather than doing data engineering _for the business_

https://www.amundsen.io/amundsen/architecture/