If Streaming Is the Answer, Why Are We Still Doing Batch?

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In this episode, Kris talks to a panel of industry experts with decades of experience building and implementing data systems. They discuss the state of streaming adoption today, if streaming will ever fully replace batch, and whether it even could (or should). Is micro batching the natural stepping stone between batch and streaming? Will there ever be a unified understanding on how data should be processed over time? Is the lack of agreement on best practices for data streaming an insurmountable obstacle to widespread adoption? What exactly is holding teams back from fully adopting a streaming model?

Recorded live at Current 2022: The Next Generation of Kafka Summit, the panel includes Adi Polak (Vice President of Developer Experience, Treeverse), Amy Chen (Partner Engineering Manager, dbt Labs), Eric Sammer (CEO, Decodable), and Tyler Akidau (Principal Software Engineer, Snowflake).

EPISODE LINKS

TIMESTAMPS
0:00 - Intro
2:58 - Is the Lambda Architecture here to stay?
6:27 - What is preventing streaming adoption today?
10:00 - Is streaming a semantic model?
20:53 - Should we push for stream processing?
26:15 - When should we use streaming vs. batch processing?
37:10 - What is the future of stream processing?
41:48 - It's a wrap!

ABOUT CONFLUENT

#streamprocessing #current2022 #apachekafka #kafka #confluent
  1. Confluent
  2. confluent
  3. apache kafka
  4. kafka
  5. stream processing
  6. adi polak
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I really like your style Kris. It was pleasure to participate by listening . I totally agree that guest were amazing. It is my first podstact that i have watched so i am going to check another one. Thank you.

michaizdebski