Apache Kafka is a community delivered event platform for streaming, which is capable of managing trillions of events a day. What once was conceived as a messaging queue, the Kafka docker is based on the abstraction of a distributed commit log. Since being started and open-sourced in 2011 via LinkedIn, Apache Kafka has gone from a messaging queue to an event that is now a full-fledged streaming platform. The founders of Apache Kafka, confluent, brings the complete distribution of the Kafka with the confluent platform.
The confluent platform will improve Kafka with additional commercial and community features that are designed to enhance the streaming experience of both the developers and operators within the production, at a huge scale.
Can Kafka help you?
Publish and subscribe
At the heart is where the immutable and humble commit log can be found. From there, you can subscribe to it. You can publish the data to plenty of systems or even real-time applications. Different from the messaging queues, the Kafka is a fault-tolerant, highly scalable distributed system, which allows it to be used for applications like driver matching and managing passengers at Uber. You are provided with real-time analytics plus prognostic maintenance for the British Gas smart houses and even performing different services all over LinkedIn. A unique performance that makes it easy to scale from just one app to even companywide usage.
An abstraction of the circulated commit log, which is commonly found within the databases is where the Kafka can provide you with long-lasting storage. The Apache Kafka will be used as a source of truth being able to transfer data over different nodes for a highly accessible operation with one single data center or over many different availability areas.
An event streaming program that certainly wouldn’t be complete without having the ability to change the data as it arrives. The streams API that is within the Kafka is a lightweight yet powerful library which allows for letting you aggregate on the fly processing, perform joins of data all within a stream, and to create windowing parameters plus more. Perhaps best of all, it is created as a Java application that is on top of Apache Kafka, allowing your workflow to stay intact without the extra clusters that need maintenance.
The Apache Kafka is a tool that developers use as it’s simple to pick up and allows for a powerful event streaming program that comes complete with 4 APIs, which is a Producer, consumer, streams, and the connect. It is also compatible with the Operatr toolkit which developer love to use.
Quite often, the software developers will start with a single-use case. An example is using a Kafka as a message buffer to protect the legacy database that struggles to maintain with today’s big work; loads, or even using the Connect API in order to keep the database in sync with the accompanying search index engine, this processes the data as it lands with the streams API so it can surface aggregations straight back to the application.
In easier terms, the Kafka and the APIs are there to make building data-driven apps and to help manage the complex back end systems. You gain peace of mind with Kafka as your data is always fault-tolerant, in real-time and is repayable. They are helping you to quickly create by giving you a single event streaming program that will store, process, and connect the system and apps with real-time data.