In this post, we have prepared a curated top list of reading recommendations for beginners and experienced. This hand-picked list of the best Apache-kafka books and tutorials can help fill your brain this March and ensure you’re getting smarter. We have also mentioned the brief introduction of each book based on the relevant Amazon or Reddit descriptions.
- Apache Kafka (2013)
- Apache Kafka 1.0 Cookbook (2017)
- Streaming Architecture: New Designs Using Apache Kafka and MapR Streams (2016)
- Building Data Streaming Applications with Apache Kafka (2017)
- Learning Apache Kafka, Second Edition (2015)
- Apache Kafka Cookbook (2015)
- Big Data SMACK: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka (2016)
- Mastering Apache Storm: Real-time big data streaming using Kafka, Hbase and Redis (2017)
- Event Streams in Action: Unified log processing with Kafka and Kinesis (2018)
- Complete Guide to Open Source Big Data Stack (2018)
- Professional Hadoop (2016)
Apache Kafka (2013)
Apache Kafka is the platform that handles real-time data feeds with a high-throughput, and this book is all you need to harness its power, quickly and painlessly. A step by step tutorial with a practical approach.
Author(s): Nishant Garg
Apache Kafka 1.0 Cookbook (2017)
Simplify real-time data processing by leveraging the power of Apache Kafka 1.0. Apache Kafka provides a unified, high-throughput, low-latency platform to handle real-time data feeds. This book will show you how to use Kafka efficiently, and contains practical solutions to the common problems that developers and administrators usually face while working with it. This practical guide contains easy-to-follow recipes to help you set up, configure, and use Apache Kafka in the best
Author(s): Raúl Estrada
Streaming Architecture: New Designs Using Apache Kafka and MapR Streams (2016)
More and more data-driven companies are looking to adopt stream processing and streaming analytics. With this concise ebook, you’ll learn best practices for designing a reliable architecture that supports this emerging big-data paradigm. Authors Ted Dunning and Ellen Friedman (Real World Hadoop) help you explore some of the best technologies to handle stream processing and analytics, with a focus on the upstream queuing or message-passing layer.
Author(s): Ted Dunning, Ellen Friedman
Building Data Streaming Applications with Apache Kafka (2017)
Design and administer fast, reliable enterprise messaging systems with Apache Kafka. If you want to learn how to use Apache Kafka and the different tools in the Kafka ecosystem in the easiest possible manner, this book is for you. Some programming experience with Java is required to get the most out of this book.
Author(s): Manish Kumar, Chanchal Singh
Learning Apache Kafka, Second Edition (2015)
Start from scratch and learn how to administer Apache Kafka effectively for messaging. This book is for readers who want to know more about Apache Kafka at a hands-on level; the key audience is those with software development experience but no prior exposure to Apache Kafka or similar technologies. It is also useful for enterprise application developers and big data enthusiasts who have worked with other publisher-subscriber-based systems and want to explore Apache Kafka as a futuristic
Author(s): Nishant Garg
Apache Kafka Cookbook (2015)
Over 50 hands-on recipes to efficiently administer, maintain, and use your Apache Kafka installation. If you are a programmer or big data engineer using or planning to use Apache Kafka, then this book is for you. This book has several recipes which will teach you how to effectively use Apache Kafka. You need to have some basic knowledge of Java. If you don’t know big data tools, this would be your stepping stone for learning how to consume the data in these kind of systems.
Author(s): Saurabh Minni
Big Data SMACK: A Guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka (2016)
Learn how to integrate full-stack open source big data architecture and to choose the correct technology―Scala/Spark, Mesos, Akka, Cassandra, and Kafka―in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses.
Author(s): Raul Estrada, Isaac Ruiz
Mastering Apache Storm: Real-time big data streaming using Kafka, Hbase and Redis (2017)
Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm. The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems.
Author(s): Ankit Jain
Event Streams in Action: Unified log processing with Kafka and Kinesis (2018)
Event Streams in Action is a foundational book introducing the ULP paradigm and presenting techniques to use it effectively in data-rich environments. The book begins with an architectural overview, illustrating how ULP addresses the thorny issues associated with processing data from multiple sources. It then guides the reader through examples using the unified log technologies Apache Kafka and Amazon Kinesis and a variety of stream processing frameworks and analytics databases.
Author(s): Alexander Dean
Complete Guide to Open Source Big Data Stack (2018)
See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn.
Author(s): Michael Frampton
Professional Hadoop (2016)
The professional’s one-stop guide to this open-source, Java-based big data framework. Professional Hadoop is the complete reference and resource for experienced developers looking to employ Apache Hadoop in real-world settings.
Author(s): Benoy Antony, Konstantin Boudnik
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Best Books to Learn Apache Kafka
We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Library Genesis and download some Apache-kafka books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.
Real-Time Streaming with Apache Kafka, Spark, and Storm: Create Platforms that Can Quickly Crunch Data and Deliver Real-Time Analytics to Users
Author(s): Brindha Priyadarshini Jeyaraman
ID: 3362965, Publisher: BPB Publications, Year: 2022, Size: 4 Mb, Format: epub
Transactional Machine Learning with Data Streams and AutoML: Build Frictionless and Elastic Machine Learning Solutions with Apache Kafka in the Cloud Using Python
Author(s): Sebastian Maurice
ID: 3181977, Publisher: Apress, Year: 2021, Size: 4 Mb, Format: epub
Designing Event-Driven Systems: Concepts and Patterns for Streaming Services with Apache Kafka
Author(s): Ben Stopford
ID: 2284618, Publisher: , Year: 2018, Size: 5 Mb, Format: pdf
Please note that this booklist is not absolute. Some books are truly record-breakers according to Washington Post, others are drafted by unknown authors. On top of that, you can always find additional tutorials and courses on Coursera, Udemy or edX, for example. Are there any other relevant resources you could recommend? Drop a comment if you have any feedback on the list.