What Is Apache Kafka?

Apache Kafka is an open-source stream-processing software platform developed by the Apache Software Foundation, written in Scala and Java. It's designed to provide a unified, high-throughput, low-latency platform for handling real-time data feeds. Let's break down its key features and uses:

Key Features of Apache Kafka

1. Distributed System: Kafka runs as a cluster on one or more servers that can span multiple datacenters.

2. High Throughput: Efficiently processes massive streams of events (messages) with high throughput.

3. Scalability: Easily scalable both horizontally and vertically without downtime.

4. Fault Tolerance: Offers robust replication and strong durability, ensuring data is not lost and is accessible even in the face of hardware failures.

5. Publish-Subscribe Model: Implements a publisher-subscriber model where messages are published to a topic and consumed by one or more subscribers.

6. Real-Time Processing: Capable of handling real-time data feeds, making it suitable for live data pipeline applications.

7. Persistent Storage of Messages: Messages are stored on disk and replicated within the cluster for durability.

Common Use Cases

1. Messaging System: Kafka is often used as a replacement for traditional messaging systems like RabbitMQ and ActiveMQ.

2. Activity Tracking: Its ability to handle high-throughput data makes it suitable for tracking user activity in websites and applications.

3. Log Aggregation: Collects physical log files from servers and puts them in a central place for processing.

4. Stream Processing: Often used in tandem with stream processing tools like Apache Flink or Apache Storm for real-time analytics and monitoring.

5. Event Sourcing: Kafka can be used as an event store capable of feeding an event-driven architecture.

6. Integration with Big Data Tools: Easily integrates with big data tools like Apache Hadoop or Apache Spark for further data processing and analytics.

7. Microservices Communication: Acts as a backbone for communication between microservices.

Architecture Components:

• Producer: Responsible for publishing messages to Kafka topics.
• Consumer: Consumes messages from Kafka topics.
• Broker: Kafka runs as a cluster of brokers. Each broker can handle a high volume of reads and writes, and stores data on disk.
• Zookeeper: Used for managing and coordinating the Kafka brokers.

Kafka is widely recognized for its high performance, reliability, and ease of integration, making it a popular choice for real-time data streaming and processing in a variety of applications, from simple logging to complex event processing systems.

Ref: Kafka Architecture