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Small Introduction About Kafka?

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What is Kafka ?

Kafka is used for real-time streams of data, used to collect big data or to do real time analysis or both). Kafka is used with in-memory microservices to provide durability and it can be used to feed events to CEP (complex event streaming systems), and IOT/IFTTT style automation systems.

Kafka is often used in real-time streaming data architectures to provide real-time analytics. Since Kafka is a fast, scalable, durable, and fault-tolerant publish-subscribe messaging system, Kafka is used in use cases where JMS, RabbitMQ, and AMQP may not even be considered due to volume and responsiveness. 

Kafka has higher throughput, reliability, and replication characteristics, which makes it applicable for things like tracking service calls (tracks every call) or tracking IoT sensor data where a traditional MOM might not be considered.

Kafka can work with Flume/Flafka, Spark Streaming, Storm, HBase, Flink, and Spark for real-time ingesting, analysis and processing of streaming data. Kafka is a data stream used to feed Hadoop BigData lakes. Kafka brokers support massive message streams for low-latency follow-up analysis in Hadoop or Spark.

Kafka has operational simplicity. Kafka is to set up and use, and it is easy to reason how Kafka works. However, the main reason Kafka is very popular is its excellent performance. It has other characteristics as well, but so do other messaging systems. 

Kafka has great performance, and it is stable, provides reliable durability, has a flexible publish-subscribe/queue that scales well with N-number of consumer groups, has robust replication, provides Producers with tunable consistency guarantees, and it provides preserved ordering at shard level (Kafka Topic Partition). 

In addition, Kafka works well with systems that have data streams to process and enables those systems to aggregate, transform & load into other stores. But none of those characteristics would matter if Kafka was slow. The most important reason Kafka is popular is Kafka’s exceptional performance.

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posted Dec 26, 2017 by Madhavi Latha

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