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Streaming Data Pipelines with Apache Kafka
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Streaming Data Pipelines with Apache Kafka

Book Details

Format Hardback or Cased Book
ISBN-10 1633437019
ISBN-13 9781633437012
Publisher Manning Publications
Imprint Manning Publications
Country of Manufacture GB
Country of Publication GB
Publication Date Mar 4th, 2026
Print length 275 Pages
Ksh 7,000.00
Not Yet Published 0 in stock

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Data streaming doesn’t have to be complex! Kafka Connect and Kafka Streams have made it possible for any developer to start building a data streaming pipeline without needing to fiddle with low-level APIs.

Batch reports arrive too late. In a world where decisions depend on seconds, waiting for yesterday’s data is no longer enough. Streaming Data Pipelines with Apache Kafka shows you how to build real-time systems that answer now, turning every event into immediate insight. 

  • Clear streaming foundations: Understand topics, partitions, offsets, and consumer groups to start thinking entirely in events. 
  • Kafka Connect recipes: Move data in and out of databases, queues, and SaaS systems with almost no code. 
  • Custom connector walk-through: Capture every change from any HTTP API and keep downstream analytics continuously fresh and correct. 
  • Stateless and stateful streams: Transform, enrich, aggregate, and join events for split-second insights users can immediately exploit. 
  • Performance tuning toolkit: Achieve millisecond latency, sustained gigabytes-per-second throughput, and rock-solid fault tolerance in production. 

Streaming Data Pipelines with Apache Kafka delivers Stefan Sprenger’s fifteen years of real-time expertise in practical form. 

An ongoing Excellent Toys case study guides you from first connector to fully deployed production cluster. Each chapter mixes concept briefs, tested configurations, and troubleshooting playbooks you can copy today, ready. 

Finish the book able to stream database changes, enrich events, and publish actionable dashboards instantly. You will speak the language of events and deliver answers while competitors still query yesterday. 

Ideal for Java developers and data scientists new to Kafka yet hungry for real-time skills. 


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