What Is Apache Kafka, How Does It Work and Its Benefits

Thinking about data as streams is a popular approach nowadays. In many cases, it allows for the building of data engineering architecture in a more efficient way than when thinking about data as a state. But to support the streaming data paradigm we need to use additional technologies. One of the most popular tools for working with streaming data is Apache Kafka.

What is Apache Kafka?

Apache Kafka is a distributed data streaming platform that can publish, subscribe to, store, and process streams of records in real time. It is designed to handle data streams from multiple sources and deliver them to multiple consumers. In short, it moves massive amounts of data—not just from point A to B, but from points A to Z and anywhere else you need, all at the same time.

Apache Kafka is an alternative to a traditional enterprise messaging system. It started out as an internal system developed by Linkedin to handle 1.4 trillion messages per day, but now it's an open source data streaming solution with application for a variety of enterprise needs.

How does Kafka work?

Kafka looks and feels like a publish-subscribe system that can deliver in-order, persistent, scalable messaging. It has publishers, topics, and subscribers. It can also partition topics and enable massively parallel consumption. All messages written to Kafka are persisted and replicated to peer brokers for fault tolerance, and those messages stay around for a configurable period of time (i.e., 7 days, 30 days, etc.).

The key to Kafka is the log. Developers often get confused when first hearing about this "log," because we're used to understanding "logs" in terms of application logs. What we're talking about here, however, is the log data structure. The log is simply a time-ordered, append-only sequence of data inserts where the data can be anything (in Kafka, it's just an array of bytes). If this sounds like the basic data structure upon which a database is built, it is.

What are the benefits of using Apache Kafka?

At the moment Kafka is the second most active and visited Apache project used by over 100 000 organizations globally.

1.     React to customers in real-time

Apache Kafka uses Kafka Streams, a client library for building applications and microservices. It is a big data technology that enables you to process data in motion and quickly determine what is working, what is not.

2.     Use the right data

With stream processing the state of ever-changing data streams from different sources can be easily detected, maintained and act upon just in time.

3.     Scale and automate

The main selling point of using Apache Kafka solutions is their scalability. The distributed systems are easier to expand and operate as a service.

When to use Apache Kafka

Apache Kafka is built into streaming data pipelines that share data between systems and/or applications, and it is also built into the systems and applications that consume that data. Apache Kafka supports a range of use cases where high throughput and scalability are vital.

Apache Kafka can handle millions of data points per second, which makes it well-suited for big data challenges. However, Kafka also makes sense for companies that are not currently handling such extreme data scenarios. In many data processing use cases, such as the Internet of Things (IoT) and social media, data is increasing exponentially, and may quickly overwhelm an application you are building based on today's data volume. In terms of data processing, you must consider scalability, and that means planning for the increased proliferation of your data.

IT operations

IT Operations is all about data. IT Operations needs access to the data, and they need it quickly. This is the only way to keep websites, applications, and systems up and running and performing at all times. Apache Kafka is a good fit for IT Operations functions that rely on collecting data from a variety of sources such as monitoring, alerting, and reporting; log management; and tracking website activity.

Internet of Things

According to Gartner, IoT is expected to include more than 20 billion devices by 2020. The value of IoT is the actionable data generated by this multitude of sensors. Apache Kafka is designed for scalability to handle the massive amount of data expected from IoT.

E-commerce

E-commerce is a growing opportunity for using Apache Kafka, which can process data such as page clicks, likes, searches, orders, shopping carts, and inventory.