http://docs.fauststream.com/en/latest/introduction.html
One question I had is how Robinhood might be doing message passing and persistence. For example, I might have a stream, that creates more messages that needs to processed, and then eventually I would want to persist the "Table" to an actual datastore.
Thanks for pointing this out. Fixed the links. You can also find the docs here: http://faust.readthedocs.io/en/latest/
Faust uses Kafka for message passing. The new messages you create can be pushed to a new topic and you could have another agent consuming from this new topic. Check out the word count example here: https://github.com/robinhood/faust/blob/9fc9af9f213b75159a54...
Also note that the Table is persisted in a log compacted Kafka topic. This means, we are able to recover the state of the table in the case of a failure. However, you can always write to any other datastore while processing a stream within an agent. We do have some services that process streams and storing state in Redis and Postgres.
I think Storm/Flink have the concept of a "tick tuple", a message that comes every n-seconds to tell the worker to flush the table to some other store. I've been looking over the project, and I'm not sure how I would do this in Faust yet, as far as I understand the "Table" is partitioned, so you'd have to send a tick to every worker.
Very interesting project!