What is Apache Kafka Used For?

Discover a variety of Apache Kafka use cases, from activity monitoring to real-time analytics | ProjectPro

What is Apache Kafka Used For?
 |  BY Daivi

Did you know thousands of businesses, including over 80% of the Fortune 100, use Apache Kafka to modernize their data strategies?


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Apache Kafka is the most widely used open-source stream-processing solution for gathering, processing, storing, and analyzing large amounts of data. The platform has many benefits, including building data pipelines, using real-time data streams, supporting operational analytics, and integrating data from various sources. There are over 1000 use cases for Kafka, including website activity tracking, event sourcing, real-time stream processing, log aggregation, etc. This blog explores some of the most innovative applications of Apache Kafka in different industries to help you understand what is Apache Kafka used for.

What is Apache Kafka Used For?

Apache Kafka is used for diverse use cases from real-time data processing to event sourcing. Kafka usage is still expanding across a variety of business sectors. The Kafka technology works perfectly with dynamically changing data-driven businesses where large amounts of records need to be processed as they come in. Apache Kafka can be beneficial when developing distributed systems, generating operational monitoring data, and establishing event sources and tracking user behavior in real time.

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Apache Kafka Use Cases

Kafka is used by companies from various industries, from computer software to financial services, health care, government, and transportation. Let us look at some innovative Kafka use-case examples in the banking and healthcare industries.

Apache Kafka Use Cases in Banking

Below are a few examples of Kafka use cases in the banking industry-

  1. Real-time Streaming Analytics

Thousands of transaction events occur in a high-volume trading environment every second, requiring efficient data analysis. These events could be sent to Kafka in a sequential manner, and they will be stored in chronological sequence to determine real-time market metrics. Trading institutions can also use Apache Kafka and stream analytics as surveillance tools that can identify even the smallest amount of manipulation and instantly alert the proper authorities who can take action.

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  1. Fraud Detection

Frauds, unauthorized payments, and money laundering often occur in the banking industry. Banks and other financial organizations can use Apache Kafka to efficiently identify frauds, maintain their integrity, and provide customers with the highest security possible. By digging through vast data, the platform will enable systems to understand behavioral patterns autonomously. Once transactional patterns are recognized, it is simple to identify suspicious (fraudulent) transactions.

  1. Event Sourcing

In-app support options like peer-to-peer chat are available in most mobile banking apps, allowing users to interact in real time with the bank customer support team. Even with multiple concurrent users, Kafka is an excellent option for the backend event sourcing aspect of an in-app chat solution. This is due to Kafka's ability to deliver high throughput at low latencies while providing message ordering and exactly-once semantics as data integrity guarantees.

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Apache Kafka Use Cases in Healthcare

Below are a few examples of Kafka use cases in the healthcare industry-

  1. Drug Discovery

Drug discovery is a complex process that takes many years to generate outcomes. One of the primary reasons behind this delay is the need for numerous clinical trials that involve data processing and analytics on large data sets. The Pharma industry can accelerate drug development by using a massively parallel system that integrates experimental biology, artificial intelligence, automation, and real-time event streaming abilities of Kafka.

  1. Automated Disease Diagnosis

According to the World Health Organization (WHO), heart attacks and strokes account for 80% of all fatalities worldwide. Data and data mining methods can therefore help in the earlier detection of heart disease by warning patients about possible infections. Using Kafka to combine messaging, storage, and stream processing, it is possible to automate disease detection by storing and processing historical and current data. 

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  1. Real-Time Healthcare Monitoring System

In the healthcare industry, real-time monitoring and tracking techniques are crucial. A massive amount of data, known as streaming big data, is continuously generated by wearable medical devices with sensors, mobile applications, and health clouds. Due to the faster-streaming data rate, it is challenging to handle such massive amounts of data in real-time to take immediate action in an emergency using ineffective and time-consuming traditional techniques. Real-time large data stream processing is crucial to ensure an efficient and scalable solution. Medical facilities can use modern online prediction technologies to predict patients' health.  With the use of Kafka topics, these systems will apply machine learning techniques to health data events that are ingested.

There are several other applications of Apache Kafka in other industries, including retail, gas and energy, etc. Try working on some Apache Kafka projects to learn more about leveraging Kafka in real-world scenarios. ProjectPro offers industry-level Big Data and Data Science projects using Kafka and many other modern technologies curated by various industry experts.

 

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About the Author

Daivi

Daivi is a highly skilled Technical Content Analyst with over a year of experience at ProjectPro. She is passionate about exploring various technology domains and enjoys staying up-to-date with industry trends and developments. Daivi is known for her excellent research skills and ability to distill

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