Kafka provides buffering, ordering, decoupling of producers from multiple consumers. So pretty much any time you have requirements for asynchronous process, fault tolerance, and/or a common view of the order of events across multiple consumers kafka is worth a look.
Spark provides a much richer language for processing data than what you'd get with writing kafka consumers yourself. On Thu, Dec 10, 2015 at 8:00 PM, Andy Davidson < a...@santacruzintegration.com> wrote: > I noticed that many people are using Kafka and spark streaming. Can some > one provide a couple of use case > > I image some possible use cases might be > > Is the purpose using Kafka > > 1. provide some buffering? > 2. implementing some sort of load balancing for the over all system? > 3. Provide filtering /sorting of data? > 4. Simplify client connection. Easy for thousands of producers to > connect to kafka. Probably hard to do with spark streaming > 5. ??? > > Kind regards > > Andy >
