The Cloudcast

Streaming alternatives to Kafka


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Yaniv Ben Hemo (@yanivbh1, Founder/CEO at @memphis_Dev) talks about Memphis Cloud, an alternative architecture to delivering streaming data for applications.  

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SHOW NOTES:

  • Memphis.dev (homepage)
  • Getting Started with Memphis (docs page)
  • Apache Kafka vs. Memphis
  • Memphis on GitHub


Topic 1 - Welcome to the show. Tell us a little bit about your background, and what brought you to create Memphis.Dev

Topic 2 - Let’s start at the beginning. Most folks will want to know why a streaming alternative. Isn’t Kafka good enough? What challenges did you personally encounter?

Topic 3 - In reviewing the architecture, it mentions differences between a broker and a streaming stack. Can you elaborate on what that means? What components are typically needed for a proper data streaming solution?

Topic 4 - One of the common issues with Kafka I hear about is operations complexity over time. It isn’t uncommon that the more a system scales, the more complex it is to operate and also maybe the harder it is to get insights and mine for key data for instance. Have you seen this in your experience?

Topic 5 - Let’s talk use cases. How do you envision organizations using Memphis Cloud? What problems are you trying to solve in the market? Is Memphis Cloud a SaaS offering? How would it be implemented in an organization?

Topic 6 - The data management side of all of this to always be problematic. Where and how is the data managed? What does the lifecycle of the data look like and what design considerations went into this aspect?

Topic 7 - When building large distributed streaming systems, I’m sure there are trade offs and optimizations of features to consider. What are you optimizing for and what are the design tradeoffs developers need to consider?


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