datahub VS fides

Sounds like you are looking for a data catalog tool instead of db schema management tool. You can check out Amundsen (https://www.amundsen.io/), DataHub (https://datahubproject.io/)

If you are looking for schema change management tool, then you can check out Bytebase (bytebase.com). But it can't answer questions like "which collections contain links to bigmongo.user.id?"

IIUC DataHub (open source project out of LinkedIn) might be relevant here

I’m a huge fan of DataHub, the open source data catalogue spun out of LinkedIn, but it’s best thought of as an observability layer for data assets that can be shared by data engineers and analyst-types. For data users: it’s a stellar search/discovery interface (what datasets are there on this keyword, which are most broadly used across the organization, what downstream products are made with this data, what’s it usually joined to, are it’s upstream pipelines reliable). For data engineers, it’s a comprehensive asset cataloger, crawling your warehouse, orchestrator, modeling layers, features, and reports, matching the lineage into a graph where it can.

If you are looking for a data cataloguing solution, look at Datahub. Haven't used it, but heard good things about it.

What I am looking for is a solution (similar to Amundsen or [Datahub](https://datahubproject.io/)) that also allows to add tables and their metadata manually.

Hello everyone, I'm looking for an open-source data lineage app (e.g. tokern, datahubproject, openmetadata).

What about DataHub? Haven't really used it but I'm actively reading about it and about to use it for some light documentation for some small pipelines.

I’ve also been impressed with the approach of Fides, an open source privacy management framework that ties into ci/cd, though I haven’t used it myself yet. The thing about it that stood out was Fideslang, their language and taxonomy for representing data privacy primitives.

Fides is built to solve for problems like this. In its current release, you can already draft a policy in YAML using fideslang and enforce that policy to ensure engineers across a team can’t accidentally or intentionally misuse data in a way that deviates from the promises a business or application makes to its users.