What is Apache Kafka: An overview of a technology

Apache Kafka is an open-source distributed low-latency real-time event-streaming system. It allows organizations to build a robust data streaming platform, enabling them to store and manage real-time data such as online transactions, website traffic, clicks, etc. Companies can use Apache Kafka for various purposes like user activity tracking, understanding consumer behavior, and analyzing real-time data like click-through rates. The distributed time managing infrastructure of Apache Kafka lets organizations achieve cost-effective data solutions that can process big data fast with minimal downtime and data loss. It provides high throughput and low latency for processing complex events and replicates partitions to distribute data onto other servers, ensuring high fault tolerance. Apache Kafka works on the publish-subscribe method, allowing organizations to send and receive data to and from several event-driven applications. It divides high-volume data into several pieces (partitions), making it highly scalable as several partitions can serve multiple consumers. The platform offers five functionalities through Application Programming Interfaces (APIs) to process streams of events or records in real-time: publication and subscription of messages, producer API, consumer API, streams API, and connector API. It also provides a storage repository to retain events for later use. Apache Kafka's architecture consists of producers (data-generating applications), consumers (receiving data from Kafka clusters), topics (a layer of abstraction that assigns a label to similar streams of records), partitions (a data unit containing a sequence of events), and Zookeeper service (managing brokers by coordinating their activities and keeping track of their availability). The platform is used for large amounts of unstructured data, such as IoT/IIoT systems, analytics systems, financial systems, social media platforms, geo-positioning systems, telecom operators, and online games. Companies like LinkedIn, Spotify, Uber, Tumbler, PayPal, Cisco, and Netflix use Apache Kafka for big data processing. Despite its benefits, managing Apache Kafka can be challenging due to limited all-in-one monitoring tools, redundant data copies, and the inability to store historical data for long. However, it remains a valuable tool for building real-time services and data pipelines.