Welcome to the community, Raviraja! 👋 Prefect is definitely the right tool for all the use cases you've described.
Sagemaker is primarily a managed service to run ML notebooks and store/serve ML models. In contrast, you can think of Prefect more as a general-purpose workflow orchestrator that allows you to build, run and operationalize your data workflows, regardless of whether those are ML flows, data engineering flows, or simply flows automating some processes. And Prefect is not tied to AWS. Sagemaker is purely focused on ML use cases and has a much more narrow focus.
I'd recommend checking the Getting-Started resources
here. You may also check
this topic about the differences between Prefect 1.0 and 2.0. If you then have any specific questions, feel free to ask those in the
#CL09KU1K7 channel or on Discourse.