Hello Devs, Is there any content or blog post to understand the difference between Pinot vs Kafka Streams (or Spark SQL)? At a high level after reading Pinot is actually bringing off-the-shelf components which otherwise data engineers have to write on top of KAFKA streams?
I mean I can write a consumer that processes events from a stream and computes the needed analytic/metric and store it into a data store to serve. Though my application layer has to route the requests either to the streaming analytics datastore or batch analytics data store. So my understanding is Pinot abstracts these two things from the application. Is that correct? Sai
