With the growing preference for a platform that can handle data streams and act on them instantly, Apache Kafka has become one of the most popular open-source messaging technologies for event stream processing. It became a well-known software platform soon after its source code was released under license and made available for distribution. Its goal is to provide a truly cohesive, high-throughput, low-latency platform for real-time data feeds that can handle trillions of events per day. In addition to high efficiency, availability, and flexibility, event-driven architecture is one of the key reasons why Kafka has become so popular. We’ve compiled a list of the top six reasons for Apache Kafka’s popularity. Here they are:
Top Reasons For Apache Kafka’s Popularity
Previously, web-scale firms utilized various methods to cope with the large amount of data fed into the system. Things began to change, though, with the introduction of Apache Kafka. The built-in functionality, scalability, and performance aspects of Kafka have won it a significant position in the big data market as an accurate and decisive means to transfer huge volumes of data at a quick rate. The following are the top reasons for Apache Kafka’s popularity.
The four components of scalability are Event Producer, Event Processor, Event Consumer, and Event Connector, which Apache Kafka can manage. In other words, Kafka scales without requiring any shutdowns. Kafka provides fast and automatic recovery in the event of node failure. This capability makes Kafka an obvious choice for data transmission and integration in a world that deals with large amounts of real-time data today.
Kafka appears to be a publish-subscribe system capable of delivering in-order, continuous, and scalable messaging. It is extremely fast and ensures that there will be no downtime or data loss.
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Low Latency & High Throughput
Without the need for such powerful hardware, Apache Kafka as a service can manage high-volume, high-speed data with millisecond latency, which is what most new use cases require. By isolating your data streams, Apache Kafka allows you to consume data whenever you want. Apache Kafka reduces latency to just 10 milliseconds with no delayed integration. This means that you will be able to send data quickly and in real-time. Furthermore, by horizontally scaling hundreds of brokers (or servers) inside a cluster, it can manage huge amounts of data.
The Kafka cluster can cope with master and database missteps. For fault tolerance, all texts written to Kafka are persisted and recreated to peer brokers, and those texts are kept for a selectable time. Kafka Streams is built on top of Kafka’s fault-tolerance features. When stream data is saved to Kafka, it is available even if the application fails and has to reprocess it since Kafka partitions are highly available and duplicated. Tasks in Kafka Streams use the Kafka consumer client’s fault-tolerance capabilities to manage failures. If a job is executing on a system that fails, Kafka Streams will immediately resume the process on one of the remaining running instances of the application.
Kafka’s prominence has prompted numerous other programs to develop integrations with it over time. This facilitates the development of new functionality, such as the integration of third-party apps. There are as many ways to connect to Kafka and use it as there are applications. Additionally, Kafka provides methods for writing new connectors as required.
Kafka will ensure that no redundant messages are created in the topic and that messages sent by a producer to a specific topic partition are attached in the order in which they were sent. Therefore, between producers and consumers, Apache Kafka offers message delivery assurances. By modifying the offset location recording, users can apply the semantics at least once and exactly once. In any event, Kafka allows you to choose the distribution semantics you want to accomplish.
In A Nutshell,
In the realm of big data, Apache Kafka is one of the most widely used technologies. Since its initial release, Apache Kafka has gained in popularity. Users were pleased and amazed with this technology since it aided them in completing data processing and simplified subsequent steps in the process. Apart from digital unicorns, this platform has been a lifesaver for slow-growing businesses and firms aspiring to become industry leaders. Look no further than Ksolves as your Apache Kafka service provider if you want to construct a highly scalable streaming infrastructure to meet your business objectives. We’ll work closely with you to help you at every level of your application’s lifetime. Furthermore, we have extensive expertise with all elements of Kafka implementation and can customize it to your unique requirements. At Ksolves, our Apache Kafka managed services provide guaranteed outcomes and long-term deployment with the capacity to deliver solutions all around the clock. We have Apache Kafka specialists or developers in India, the United States, and other countries. What sets Ksolves apart from its rivals is its partnership with the Apache Foundation to provide a seamless installation and mentorship of Apache Kafka.
Apply the best of Apache Kafka to your company to discover your company’s bright future!
AUTHOR
Apache Kafka
Anil Kushwaha, Technology Head at Ksolves, is an expert in Big Data and AI/ML. With over 11 years at Ksolves, he has been pivotal in driving innovative, high-volume data solutions with technologies like Nifi, Cassandra, Spark, Hadoop, etc. Passionate about advancing tech, he ensures smooth data warehousing for client success through tailored, cutting-edge strategies.
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