Best Apache Kafka Books to Buy in October 2025
Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale
Apache Kafka in Action: From basics to production
Mastering Kafka Streams and ksqlDB: Building Real-Time Data Systems by Example
Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale
Effective Kafka: A Hands-On Guide to Building Robust and Scalable Event-Driven Applications with Code Examples in Java
Kafka in Action
Streaming Architecture: New Designs Using Apache Kafka and MapR Streams
Apache Kafka At the Gates of Mastery: Kafka Core
Real-Time Streaming with Apache Kafka, Spark, and Storm: Create Platforms That Can Quickly Crunch Data and Deliver Real-Time Analytics to Users (English Edition)
If you're curious about Apache Kafka, you've come to the right place! In short, it's an open-source streaming technology platform that runs things such as Netflix, AirBnB, Target, Pinterest, and even Microsoft. However, it doesn't stop there, as this tech is behind some of the most popular, event-driven, and real-time user experiences on the web to date. So, let's explore Apache Kafka in more detail and gain some insight as to how it works, what it's used for, and how someone might be able to utilize it themselves.
What is Apache Kafka Used For?
Officially speaking, it's called a distributed streaming platform. This means that many machines work together to receive and produce data, allowing applications to read the stored data and send it to the user. Let's break that down just a little more and make it easier to understand.
Billions and billions of data records out in the digital world today are being continuously streamed and stored, including real-time events. Actions such as ordering something online, submitting registration forms, or even a smart home making a decision are all real-time events that require data storage and distribution - whether a person is involved or not. The Apache Kafka platform allows for massive quantities of real-time event data to be stored or used simultaneously without any lag. The volume of data and events coupled with the seamless experience it provides is what makes Apache Kafka so appealing and increasing in popularity.
Its topics are partitioned and replicated in a way that scales up to massive quantities of data without negatively impacting performance. Whether you're dealing with nothing more than a few megabytes or a massive array of terabytes, Kafka will perform the same across the board.
Not only does it process data in real-time, but it stores the data accurately, durably, and sustainably. Thus, much of its commercial use is within two specific types of applications: real-time streaming data pipelines and real-time streaming applications. A data pipeline app is specifically designed to move millions and millions of data at high speeds; Apache Kafka is reliable for this because it reduces the risk of corruption or duplicate data, giving developers and producers peace of mind that they won't have any extra legwork. A streaming app is anything that continuously updates its online presence, from retail or grocery stores to ads displayed from analysis of your clicks; this allows a seamless consumer experience.
To sum up what Apache Kafka is: a fault-tolerant, highly scalable, and highly reliable data distribution technology. Applications publish, consume, process, and distribute massive volumes of data from producers to users in real-time.
Is Apache Kafka Difficult to Learn?
Absolutely, yes. It's difficult, but it's not impossible. If you're new to learning Kafka or coding in general, it can be challenging to grasp every aspect, such as brokers, clusters, topics, partitions, and logs. Producers and consumers work independently; data published by producers is stored, rather than deleted, to ensure they're available for consumers for some time. Most conventional message broker systems tend to delete data once it's processed.
Much of what Apache Kafka employs is totally new to developers, making it a bit of a learning curve if you're new to the data scene as a whole.
However, the beautiful thing about Kafka is its open-source availability. It's out and ready to be learned by anyone, and there are hundreds of resources on how to do just that! Dedicated developers have created everything from online courses on the subject to whole forums full of questions and answers. The truly determined and curious only need to do some digging to find what they're after.
Is Kafka Written in Java?
Yes! It was initially written in Scala, but the problem was that Scala didn't maintain binary compatibility between versions. It was updated to transition Scala APIs to Java APIs; it can be used with both and more.
Which Language is Best for Kafka?
Ultimately, that's up to you! Apache Kafka can be used with Java, Scala, Python, .NET, Go, C/C++, and many more. In addition, some uncommon but still useful code languages utilized for it are PHP, Erlang, Groovy, Haskell, Rust, Ruby, and even more than that. Most consider Java to be the most useful, as it is the most mainstream. Still, the open-source tech is so easily customizable that many developers have used it in nearly every coding language available.
Apache Kafka may be slightly difficult to comprehend at first, but it's here to stay. As a practical and durable data processing and streaming platform, its uses in the digital sphere are only quantified by what developers want to do with it. However, almost anyone can learn to use it in their preferred coding language with a bit of perseverance.