Developed by the Apache Software Foundation and written in Scala is an open source message broker known as Apache Kafka. The project was initiated to provide a high throughput, unified and low latency platform that is capable of handling real time feeds. It is basically a pub / sub message queue that is immensely scalable and built as a distributed transaction log, thus, providing great value to enterprises endeavouring to process the streaming data.
This high throughput messaging system running as a distributed commit log has the following features:-
1. Highly Scalable
With Apache Kafka, a single cluster can serve as the central backbone for data even for a very large organisation. Without causing downtime, it can expand easily and in the most transparent manner. The data streams are segregated and dispersed over a cluster of machines to permit data streams that are greater than the capability of a single machine.
2. Extremely Fast
Designed to run at super fast speeds, the Kafka allows a broker to handle petabytes of reads and writes pertaining to thousands of clients every second.
3. Durable & Reliable
To protect the data from loss, messages are written on a disk and even copied within the cluster. Without adversely impacting the performance, Kafka brokers can handle humongous volumes of data.
4. Hosts Cluster-Centric Design
Kafka is endowed with cluster centric design for greater durability and comes with fault tolerance guarantee.
Apache Kafka As One Of The Three Distributed Systems For Creating Real Time Trinity
As the world is pacing ahead to incorporate more of technological devices in their routines, the demand for more intelligent and real time mobile applications is on the constant rise. The basic purpose of these applications is to offer pertinent and immediate delivery of information and services. In order to keep pace with the data flowing in from various sources, streaming of data by applications must possess a real time infrastructure for capturing, processing, analyzing and delivering the huge amounts of data to millions of users.
To create a real time trinity, leading deployments make use of three distributed systems such as a messaging system, transformation tier and an operational database. The messaging system helps in capturing and publishing feeds, the transformation tier filters information, improves data and delivers in the right format to the right audience and the operational database stores the data while easing application development and analytics.
One perfect example of an efficient messaging system is Apache Kafka that acts as a broker between the consumers and producers of message streams. Being a distributed system, the Apache Kafka is capable of scaling the number of producers and consumers by including more servers. With commit log to disk and full utilisation of the Kafka’s memory attaining high level of performance efficacy in real time data pipelines with increased durability is possible, even in case of any downtime or server failure.
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