Developed by LinkedIn and later donated to Apache, Kafka has now become the de-facto standard for a majority of companies when it comes to real-time big data analytics.
It is LinkedIn has deployed one of the largest clusters of Kafka that was used to ingest more than 1 billion events per day.
Can you guess what this number has reached recently?
It's a whopping more than 1.1 trillion!!
There is no doubt that the popularity of Apache Kafka is increasing at an exponential rate that has an ingestion rate of more than 1 trillion messages per day. It has now entered the four-comma club. Not only LinkedIn, but some of the biggest names are also deploying Kafka for streaming data in real-time including Netflix, Mozilla, Twitter, and Oracle.
The increasing deployment of Kafka in companies has broadened the career landscape in this domain. By acquiring Kafka Certification, you can choose to become Big Data Architect in Kafka, Kafka Project Manager, Kafka Developer, or Kafka Testing Professional.
Before moving towards the actual question of the topic, let’s first have an overview of Apache Kafka.
What is Apache Kafka?
Apache Kafka is an open-source, distributed data store that is optimized for processing and ingesting streaming data in real-time. It is actually a message-broker program that is written in Scala.
The main objective of Kafka is to provide a unified, low-latency, high-throughput platform that can handle real-time data feeds.
How did Kafka come into existence?
With increasing data generation across the world, companies found it challenging to analyze such huge amounts of data. Before analysis, the data has to be properly collected for a system to process it. It has now become mandatory to collect real-time data in order to reflect the current condition of the business.
Real-time data has become a significant factor in quantifying performance and then making smart business decisions. Streaming data refers to the data that is continually generated by numerous data sources meant to send in the data records simultaneously. A streaming platform should be capable of handling this consistent influx of data to possess it incrementally as well as sequentially.
It is here that Kafka comes into action by building real-time data pipelines and applications that can easily adapt to these data streams. To enable the collection, storage, and analysis of existing and real-time data, Kafka combines messaging, storage, and stream processing systems.
Apache Kafka is generally used as a message broker platform that enables processing and communication between two applications.
Apache Kafka Architecture
To process real-time streaming data, Apache Kafka is often integrated with Apache Spark, Apache Storm, and Apache HBase. It can deliver huge message streams to the Hadoop cluster irrespective of the use case or industry.
Kafka is typically deployed as a cluster that is implemented on one or more servers. This cluster can store topics that comprise streams of messages or records. Every record holds a key and a value. Brokers are basically abstractions that are used to manage the replication and persistence of the message.
The four core APIs of Apache Kafka include:
● Producer API allows applications to publish a stream of messages or records to one or more topics
● Consumer API enables these applications to endorse one or more topics and then process the stream of messages
● Streams APIs are generally stream processors that get the input from topics, convert the input streams to the output streams, and produce the output to the related topics
● Connector API processes and executes reusable consumers and producers that are able to connect topics to the existing applications. This way, it allows users to automate the addition of another data system
Benefits of Apache Kafka
There are many significant benefits of using Kafka’s approach to real-time Big Data Analytics. Some of them are:
Highly Scalable: the partitioned log model of Kafka lets data be distributed across various servers making it much more scalable than that in a single server.
Web activities tracking: Kafka keeps track of web activities to be processed in real-time such as storing or sending events.
Continuous Streaming: it continuously processes streaming data
Standard Format: it can convert data of different formats to a standard format in order to eliminate ambiguity.
Fault-tolerant: being resilient to node failures and highly available, Kafka is a fault-tolerant message broker system that supports automated recovery
Low Latency: Kafka can reduce the latency significantly and allows you to deliver data within fractions of seconds in real-time.
High Throughput: Kafka is popular for its ability to handle massive volumes of data at high velocity. Kafka is capable of handling thousands of messages per second which implies that it boasts the feature of high throughput.
Durable: Kafka is durable in the sense that it allows you to replicate your messages that can persist quicker on the disk, even after being processed.
Prerequisites for Learning Apache Kafka
IT professionals looking for a career in Big Data can learn this revolutionary message-brokerage system meant to work with real-time data. Also, you can pursue a Kafka training course if you are in any of the positions that include IT Developer, Researcher, Analytics Professional, tester, or an individual willing to make a transition to their career in this domain.
As far as educational pre-requisites are concerned, you should possess a high-school diploma or undergraduate degree in the field of computer science, information technology, or any related field.
Now the question comes, ‘is the knowledge of Java essential for learning Kafka?’.
The answer is YES.
It is essential to have prior knowledge of Java or any other programming language. Also, you should possess the knowledge of any messaging system and Unix or Linux-based systems.
Conclusion
By going through the figures and facts mentioned in the article, it is clear that many tech giants are looking for professionals who are highly skilled and trained in this trending technology called Apache Kafka.
To learn the concepts and working of this messaging system you can take up an online training course from an accredited institute. You can consider enrolling yourself in the Apache Kafka Certification Training course by Simplilearn lets you explore the different ways of processing massive amounts of data with different tools. With Kafka training, you will learn how to leverage Big Data Analyst in order to get maximum benefits.
Enroll Yourself Now!!
No comments:
Post a Comment