I am setting up mlflow server with Postgres and S3 on AWS ECS(or AWS EC2) for personal usage. I would like to know if using Postgres would actually give me any benefit?
as shown in scenario 5 in docs, I would like to set up server with proxied artifact storage, but without postgres in AWS RDS and also not in `--artifacts-only` and `--artifacts-only` modes as shown in scenario 6 in docs. So, if i launch a mlflow tracking server like this, will all the metadata that usually gets saved to an SQLAlchemy database(postgres in my case) be saved to the location of attribute `--artifacts-destination` as files?
I would like to do this to save costs from AWS RDS that runs Postgres.
If you aren't familiar with AWS ECS, it is a fully managed service (a simpler version of kubernetes) that runs container base applications. and EC2 is just user managed machines or servers.