What Is Apache Kafka?

Definition: Apache Kafka

Apache Kafka is an open-source stream-processing software platform developed by the Apache Software Foundation, written in Scala and Java. The project aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds. Kafka is fundamentally designed to allow a single cluster to serve as the central data backbone for a large organization.

Introduction to Apache Kafka

Apache Kafka was originally developed by LinkedIn and later became part of the Apache Software Foundation in 2011. It is widely recognized for its high performance, scalability, and fault tolerance. Kafka is used primarily for building real-time streaming data pipelines and applications that adapt to data streams. Its capabilities make it an essential tool for data-intensive applications across a wide range of industries.

Key Features of Apache Kafka

Distributed System

Kafka runs as a cluster on one or more servers that can span multiple datacenters. The Kafka cluster stores streams of records in categories called topics.

High Throughput

One of Kafka’s key features is its ability to handle high volumes of data while maintaining low latency. This is achieved through the efficient handling of data and the use of a simplistic routing approach.

Scalability

Kafka clusters can be expanded without downtime. New nodes can be added and data can be rebalanced among these nodes as they join the cluster. This allows Kafka to grow with the needs of its applications.

Fault Tolerance

Kafka is designed to be fault-tolerant. It replicates data and can handle failures of nodes in the cluster without losing data.

Durability

Kafka uses a distributed commit log, meaning messages persist on disk as fast as possible, providing intra-cluster replication and hence durability. This ensures that data is not lost and can survive broker failures.

Real-Time

Kafka is capable of handling real-time data feeds with effectively no lag. This is crucial for applications that rely on timely and accurate data for processing.

Uses of Apache Kafka

Messaging

Kafka is widely used as a replacement for more traditional message brokers, like AMQP and JMS, due to its higher throughput, reliability, and replication.

Activity Tracking

Its ability to handle high volumes of data in real-time makes it ideal for activity tracking applications. Kafka can collect user activity data from websites and apps in real time.

Gather Operational Metrics

Kafka can aggregate statistics from distributed applications to produce centralized feeds of operational data.

Stream Processing

With Kafka, you can process streams of data in real time. This is useful for real-time analytics and monitoring applications.

Event Sourcing

Kafka can be used for event sourcing, which involves capturing all changes to an application state as a sequence of events.

Benefits of Apache Kafka

• Reliability: Kafka is distributed, partitioned, replicated, and fault-tolerant which enhances its reliability.
• Scalability: It can handle large numbers of messages without incurring a significant performance hit.
• Performance: Kafka has high throughput for both publishing and subscribing messages. It maintains stable performance even many TB of messages are stored.
• Durability: Kafka uses a distributed commit log, which means that messages are safe and won’t be lost.

Frequently Asked Questions Related to Apache Kafka