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Top 10 Benefits of Apache Kafka

What is Apache Kafka?

Apache Kafka is a fast, scalable, durable, and fault-tolerant publish-subscribe messaging system used to manage big volumes of data. Due to high efficiency, reliability and replication characteristics, Kafka is applicable for systems like tracking service calls (tracks every call), instant messaging or tracking IoT sensor data where a traditional technology might not be considered. Kafka can work with different frameworks for real-time ingesting, analysis, and processing of streaming data. Kafka is also a data stream used to feed Hadoop Big data lakes.

Overview of Apache Kafka

Originally designed as a messaging system, Apache Kafka has evolved to be a full-fledged event streaming platform. It is a distributed event streaming platform that can handle trillions of events every day. This platform is the best option on the market for any business or industry that is considering highly scalable, real-time data solutions to build and manage data pipelines. With low downtime issues and huge data storage, makes it easier and more stable to handle a huge volume of data.

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Overview of why Kafka matters

What are the benefits of Apache Kafka?

  1. Acts as a buffer: Apache Kafka solves data transformations process by acting as an intermediary, receiving data from source systems and then making this data available to target systems in real-time. During this process, systems will not crash because Apache Kafka is on its own separate set of servers called an Apache Kafka cluster.
  2. Highly scalable: Kafka is a distributed system, which can be scaled quickly and easily without incurring any downtime.
  3. Highly reliable: Kafka replicates data and can support multiple subscribers. Additionally, it automatically balances consumers in the event of failure. That means that it is more reliable than similar messaging services available.
  4. Low latency: Apache Kafka decouples the message which lets the consumer to consume message anytime. This leads to low latency value, up to 10 milliseconds.
  5. Offers high performance: Due to low latency, Kafka can handle a huge number of messages of high volume and high velocity. Delivers high throughput for both publishing and subscribing, utilizing disk structures that are offering constant levels of performance, even when dealing with many terabytes of stored messages.
  6. Fault tolerance: Kafka has an essential feature to provide resistant to node/machine failure within the cluster.
  7. Reduces the need for multiple integrations: All the data that a producer writes go through Kafka. Therefore, you just need to create one integration with Kafka, which automatically integrates all users with each producing and consuming system.
  8. Easily accessible: As all our data gets stored in Kafka, it becomes easily accessible to anyone.
  9. Distributed system: Apache Kafka contains a distributed architecture which makes it scalable. Partitioning and replication are the two capabilities under the distributed system.
  10. Real-time handling: Apache Kafka can handle real-time data pipeline. Building a real-time data pipeline includes processors, analytics, storage, etc.

Sources:

https://www.confluent.io/online-talks/benefits-of-stream-processing-and-apache-kafka-use-cases/

https://blog.udemy.com/4-key-benefits-of-apache-kafka-for-real-time-data/

https://www.ibm.com/blogs/nordic-msp/understand-apache-kafka-and-its-advantages/

https://dzone.com/articles/what-is-kafka#:~:text=Why%20Kafka%3F,due%20to%20volume%20and%20responsiveness.

https://techbeacon.com/app-dev-testing/what-apache-kafka-why-it-so-popular-should-you-use-it

https://www.precisely.com/blog/big-data/4-benefits-of-using-apache-kafka-in-lieu-of-amqp-or-jms

https://www.javatpoint.com/apache-kafka-advantages-and-disadvantages

https://kafka.apache.org/uses

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