What is Apache Kafka? A Comprehensive Guide to its Importance & Career Opportunities

The simplest definition of Kafka is that it is an open-source distributed streaming platform that serves data continuously. Developed by LinkedIn, written in Java and Scala, and then open-sourced to Apache Foundation in 2012, Kafka’s main contributor is still LinkedIn.

As opposed to batch data, which can be historical data stored in databases, streaming data is continuously generated by multiple sources continuously ordered in time. At LinkedIn, Kafka was initially created to simplify activity tracking and gather logs and application information. That is way back in 2011. So, Kafka is not a new technology, but it is a proven technology that has stood the test of time and has improved over the years.

With Apache Kafka, you can create applications and data pipelines that respond in real-time.

This means you can make faster decisions and give customers a better experience. Kafka also allows you to process, store and analyze streaming data. It can also be used for stream processing and log aggregation, which helps build complicated data pipelines, do real-time analytics and make informed data-driven business decisions.

This is what a simplified look of Kafka looks like as a system sourcing and distributing data in real-time analytics.

Kafka's unique Publisher and Subscriber (Pub/Sub) messaging system has allowed developers to build complex and distributed real-time data systems with ease.

Kafka is helpful in multiple applications as follows:

• Kafka applications can use Kafka to stream data or events and publish or subscribe to them.
   
• Kafka accurately stores data records and is very fault-tolerant.
   
• Kafka has the capacity to process large amounts of data quickly.
   
• Without experiencing any performance concerns, Kafka can accept and analyze trillions of data records each day.

Let us dial it down a bit and understand what this technology is and its power.

Apache Kafka is a special technology that helps to move information from one place to another place pretty quickly (remember the unending stream of information as you scroll through LinkedIn!). 

Now, let us talk about real-time analytics. 

That is another way of referring to the state when you want to analyze data as it is getting generated, like in the Now. Let us say you have a website, and you want to know how many people are visiting it and where are they coming from at any given moment. You need to check that data in real-time to know what is happening.

And this is where the power of Apache Kafka shines through. 

It can quickly and easily send data from your website to a place where you can analyze it in real time. You can see how many people are visiting your site at this moment, where are they coming from, which pages they are interacting with the most, which pages they are landing on, and which keywords are being used to land. All that information can be analyzed based on the data that is gathered and served. 

Overall, Apache Kafka is like a superfast mailman that helps us quickly move mail from one place to another, which is helpful for real-time analytics! 

Kafka is a popular technology because it makes it easier for companies to manage their data, especially when they need real-time data analytical needs.

It is like a big filing cabinet for data. 

Instead of having to store data in multiple places and manually transfer them, Kafka helps companies store all the data in one place and transfer it at lightning speeds. This enables companies to analyze their data quickly and get reliable insights from it. 

This means that a company can use Kafka to store all of their customer data in one place, as they are getting generated on a daily basis without the fear of losing any data. And then quickly analyze it to glean information and insights about their customers. This kind of ability to generate intelligence from data on a real-time basis enables companies to better understand their customers and make informed decisions to add capabilities to their products or services.

Are you into playing online games? Then the below example helps you understand the popularity of Kafka better.

Imagine you are playing an online video game with your friends. Your computer must know what your friends are doing within the game, so you can play together, irrespective of which part of the world your friends have logged in from. When someone does something in the game like shoot a gun, that message needs to get sent over to all the other players in the game, so they play their game based on this information. This has to happen almost instantaneously. 

Apache Kafka can, in such a scenario, help send those updates almost instantaneously, so you do not have to wait long for your friends’ actions to show up on your computer.

So, Apache Kafka is popular because it helps companies share data between different systems in real time. This will be extremely helpful for needs such as tracking customer behavior, monitoring financial transactions, or even just playing video games, as stated above.

Kafka is not required for all businesses but is critical for the success of those companies that need capabilities to capture, store, and transfer the data securely and then analyze this large amount of data as it is being generated and derive business intelligence from it.

Now, although this technology has been around for over a decade, its importance has been growing in the recent past, which makes the ability to work with Apache Kafka, a powerful tool for developers that work with data.

You can learn Kafka to develop business solutions, and you will have the skills needed to create powerful apps and websites that can process data quickly, securely, and reliably. This is also helpful because, typically, systems consist of a technology stack, and Kafka is just a part of the entire stack. You should be able to write applications in Kafka and integrate them with other components of the system. The best way to learn Apache Kafka is by gaining hands-on experience with the technology through practical projects and exercises.

If you want to build something like a cool video game or big online marketplace or even wish to work for LinkedIn, it is important to learn Apache Kafka so you know how to work with applications and systems that need real-time data-handling capabilities. Having a basic understanding of distributed systems and programming languages such as Java, Python, or Scala is recommended as a prerequisite to effectively learning Apache Kafka.

Therefore, learning Apache Kafka is important for you as a beginner, as it helps you build faster and more efficient software applications. It helps you think better as an application developer as well as a database engineer, which, being a rare combination, will help you grow fast in your career. There are many courses on Kafka available online, ranging from beginner to advanced levels, to help you build your Kafka skills and knowledge.

The Apache Kafka Certification and Confluent Certified Developer for Apache Kafka are two of the most well-known certifications in Kafka programs available. The Confluent Certified Developer for Apache Kafka (CCDAK) course covers advanced topics such as Kafka Streams and Kafka Connect, in addition to Kafka core concepts. The Apache Kafka (CCDAK) certification is a comprehensive and reputable program that can boost your Kafka development skills and credibility.

• Apache Kafka Fundamentals by Whizlabs
  Start by learning This Kafka course is offered by Whizlabs and contains hands-on training. This is geared toward beginners, and you get lifetime access to this course.
   
• Apache Kafka for Beginners - Learn Kafka by Hands-On by O’Reilly
  Once you understand the fundamentals, as a beginner, you should consider this Kafka course. Although the name suggests that this is for beginners, this course is aimed at an intermediate level. That is why the first course becomes important for you to take as a precursor to this one.
   
• Apache Kafka - Real-time Stream Processing (Master Class) by O’Reilly
  This is one of the popular and trending courses on Apache Kafka. This contains over 10 hours of hands-on training and expects you to have fundamental knowledge as a prerequisite.
   
• Apache Certification Training Course by Edureka
  If you need a certification to signal your credibility, then this program by Edureka is the one to consider. This is a 5-week Kafka course, which is conducted by an instructor. This is one of the most popular certification courses to learn Apache Kafka. If you are considering only one course to understand Kafka, this should be it.
   
• Apache Kafka Series - Kafka Cluster Setup and Administration by O’Reilly
  This course includes the fundamentals of Kafka and hands-on training in setting up the data-processing Kafka clusters and learning administration.

Apache Kafka is a technology that helps to capture, store, transport, and process data securely in real-time. This is a high-value skill. 

Here are the top 5 career opportunities that you can pursue after learning Apache Kafka:

• Apache Kafka Developer
  Apache Kafka Developers implement streaming data solutions using Apache Kafka as per the architecture and design given to them. In this role, you will write code to create real-time data pipelines and streaming applications to process data. This job involves building and maintaining software systems that use Kafka as part of the technology stack. 
   
• Database Engineer
  Database Engineers design and build large-scale data processing systems using Apache Kafka. They use Kafka to create real-time data pipelines and stream data from various sources.
   
• Data Scientist
  If you have learned all Kafka basics, and are skilled in Kafka, becoming a Data Scientist gets a little easier. Data Scientists use Apache Kafka to analyze large volumes of streaming data and build predictive models. They use Kafka to create real-time data pipelines and stream data from various sources.
   
• Big Data Architect
  Big Data Architects design and build large-scale data processing systems using Apache Kafka to be used in Big Data solutions. They use Kafka to create real-time data pipelines and stream data from multiple data sources. They use this to build predictive models that can help businesses make decisions in real time.
   
• Business Intelligence Analyst
  Business Intelligence Analysts use Apache Kafka to analyze streaming data and create visualizations. This job involves working with data as it is generated to provide insights to businesses in real-time. You will work with tools to collect and analyze data as it comes in.

You can work at different levels, contributing to different areas of specialization, as explained above.

• The average annual pay for a Kafka Developer in the USA is around $133,744 a year.
   
• The average annual pay for a Kafka Developer in the UK is around £67,500 per year.
   
• The average annual pay for a Kafka Developer in India is around ₹5,00,000 lakhs per year, and with experience can go up to ₹23,00,000 lakhs per year.

Please note that salaries can vary widely depending on specific factors such as the company, industry, and job level.

As the technology matures, the combination of various technology and business problems leads to the creation of new solutions. The demand for Apache Kafka has been steadily increasing over the years.

The messaging and event-streaming software industry is expanding quickly, with a Compound Annual Growth Rate (CAGR) of 26.9%. According to IDC, it is anticipated to increase from $1.6 billion in 2019 to $5.3 billion in 2025. 

Source: Google Trends

Google trends show that the interest and adaptation of Apache Kafka have been steadily increasing over the years. 

With the demand for real-time streaming data in various industries, such as Gaming and Communication, business-critical applications are pushing the demand for Apache Kafka. It will continue to grow over the coming years as organizations look to unlock the potential of streaming data for more business-critical applications.

According to a survey conducted by Confluent, 70% of participants said they were very satisfied with using Apache Kafka to develop real-time data processing applications.

Around 72% of respondents said that Apache Kafka is most commonly used for stream processing. In addition: 

• Around 67% of participants said that Kafka helped their applications work together in a loosely coupled manner.
   
• Around 59% of participants said that they use Kafka as an underlying data infrastructure for stream-processing solutions.
   
• Around 58% of participants said that Kafka brought much-improved scalability to their applications.
   
• Around 51% of participants said that high volumes of data are now available in real-time and that they are able to move beyond batch-processing constraints.

Kafka boasts 41.01% of the market share in Queueing, Messaging, and Background Processing space! The next best technology is RabbitMQ, which only has a 29.96% market share, with a whopping 12% difference between them.

Over 23,640 customers have implemented data processing applications using this Apache Kafka in their technology stack.

In recent years, Apache Kafka has become widely popular among developers and enterprises, especially for its ability to manage high volumes of data in real-time, and no other technology has been as efficient.

According to a survey conducted by Confluent, a leading provider of Apache Kafka, the demand for Kafka has increased consistently, with 86% of respondents indicating that they are increasing their use of Kafka technology. As much as 52% of the organizations have implemented at least 6 systems with Kafka as the technology stack!

• Multi-Cloud Deployments are Becoming More Important
  For analytics, data compliance guidelines, and a quicker reaction to shifting business conditions, large firms with operations spread over many different geographic locations must update their database event logs.
   
• Increased Focus on Streaming Live Events
  Applications in areas like financial and retail data are increasing, for optimizing pricing and revising company decisions in light of fresh sales trends. Data from the cloud and corporate suppliers are connected through Kafka, which collects the data and feeds it to other types of software for in-depth analysis of distributed events.
   
• Development of Microservices
  Microservice development for hybrid clouds and multi-clouds is a growing area of application development. These cloud-native applications work with data-in-motion before saving application outcomes as data-at-rest in business databases, using containers and Kubernetes management.

Apache Kafka is an open-source stream-processing software that's widely used for collecting, processing, storing, and analyzing data. It offers several benefits, including high throughput, low latency, and fault tolerance, making it capable of handling thousands of messages per second. With over 1,000 Kafka use cases implemented in different industries and applications, it's the industry standard for event stream processing. 

Obtaining a certification can demonstrate your expertise in the technology and increase your career opportunities in real-time analytics. Some of the companies that use Kafka include Goldman Sachs, Box, LinkedIn, Netflix, and Cisco. As one of the most trusted technologies for empowering companies, Kafka allows organizations to drastically improve their data collection, processing, and analytics strategies with event streaming architecture.

The demand for people with skills in this technology is growing, making it a great career choice for those interested in the real-time data analytics field.