AWS Step Functions

We have some lambdas we need to orchestrate to get our workflow going. In the past, we already attempted to use Airflow as the orchestrator, but the need to coordinate the tasks in a database generates an overhead that we cannot afford. For our use case, there are hundreds of inputs per minute and we need to scale to support all the inputs and have an efficient way to analyze them later. The ideal product would be AWS Step Functions since it can manage our load demand graciously, but it is too expensive and we cannot afford that. So, I would like to get alternatives for an orchestrator that does not need a complex backend, can manage hundreds of inputs per minute, and is not too expensive.

What's the difference between AWS Lambda and AWS Step Functions?

I am working on a project that grabs a set of input data from AWS S3, pre-processes and divvies it up, spins up 10K batch containers to process the divvied data in parallel on AWS Batch, post-aggregates the data, and pushes it to S3.

I already have software patterns from other projects for Airflow + Batch but have not dealt with the scaling factors of 10k parallel tasks. Airflow is nice since I can look at which tasks failed and retry a task after debugging. But dealing with that many tasks on one Airflow EC2 instance seems like a barrier. Another option would be to have one task that kicks off the 10k containers and monitors it from there.

I have no experience with AWS Step Functions but have heard it's AWS's Airflow. There looks to be plenty of patterns online for Step Functions + Batch. Do Step Functions seem like a good path to check out for my use case? Do you get the same insights on failing jobs / ability to retry tasks as you do with Airflow?