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Introducing Kafka Streams: Stream Processing Made Simple

Blog post from Confluent

Post Details
Company
Date Published
Author
Victoria Xia, Jay Kreps, Wade Waldron
Word Count
4,973
Company Posts That Month
3
Language
English
Hacker News Points
2
Post removed?
No
Summary

The Kafka Streams API simplifies building streaming applications by providing a cluster- and framework-free library that can be used with existing Kafka clusters. This approach reduces operational complexity, making it easier to build and deploy critical core applications and microservices that process real-time data streams. The API integrates tables and streams, allowing for the computation of derived values against table updates using just the stream of changes. It also simplifies windowing, time, and out-of-order events by representing windows as updatable quantities stored in a table. This enables transparent maintenance of derived state, allowing applications to directly query local aggregates. The overall goal is to make stream processing accessible as a mainstream application programming model for asynchronous services, reducing the complexity associated with traditional stream processing frameworks.

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