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Designing Data Intensive Applications - Chapter 11 (Stream Processing Part 2)

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Designing Data Intensive Applications - Chapter 11 (Stream Processing Part 2) event
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Chapter 11 - Stream Processing Part 2

In this #taro-bookclub discussion, we'll go over Chapter 11 of "Designing Data-Intensive Applications" by Martin Kleppmann. This chapter is about stream processing. In part 1 of the chapter we covered the following concepts:

  • Message Brokers / Queues - Log-based Message brokers vs AMQP/JMS brokers
  • Message Delivery Patterns
  • Change Data Capture implemented as event stream to keep multiple data stores in sync
  • Introduction to Event Sourcing

Here's the agenda for part 2:

  • Continue converstation on event streaming
  • Use cases of stream processing
  • Creating compound streams by combining streams with other streams and databases.
  • Challenges faced in stream processing in large scale data systems - Message Ordering, Fault Tolerance etc.
  • There will also be time for any questions and answers you might have.

Please send your questions ahead of time to Raj Shah in the Taro Premium Slack, so that they can be included in the discussion.

Get ready for another engaging and informative session!