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Do I really need Kafka?

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Do I really need Kafka?

Where you usually need Kafka is if you have a LOT of data that you need to process very quickly and send somewhere else. Kafka can also store as a retention mechanism, keeping data for 2,3, or even 7 days – that way if your downstream processes fail, you can reprocess using what’s in Kafka.

Who uses Kafka and why?

Today, Kafka is used by thousands of companies including over 60\% of the Fortune 100. Among these are Box, Goldman Sachs, Target, Cisco, Intuit, and more. As the trusted tool for empowering and innovating companies, Kafka allows organizations to modernize their data strategies with event streaming architecture.

Why Kafka is better than JMS?

Apache Kafka is more suitable to handle a large volume of data due to its scalability and high availability while JMS systems are used when you need to work with multi-node clusters and highly complicated systems.

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Why do we need Kafka streaming?

Kafka Streams is a library for building streaming applications, specifically applications that transform input Kafka topics into output Kafka topics (or calls to external services, or updates to databases, or whatever). It lets you do this with concise code in a way that is distributed and fault-tolerant.

What is Kafka streams used for?

What is the difference between MQ and Kafka?

While ActiveMQ (like IBM MQ or JMS in general) is used for traditional messaging, Apache Kafka is used as streaming platform (messaging + distributed storage + processing of data). Both are built for different use cases. You can use Kafka for “traditional messaging”, but not use MQ for Kafka-specific scenarios.

What is the actual use of Kafka?

Messaging. Kafka works well as a replacement for a more traditional message broker.

  • Website Activity Tracking. The original use case for Kafka was to be able to rebuild a user activity tracking pipeline as a set of real-time publish-subscribe feeds.
  • Metrics. Kafka is often used for operational monitoring data.
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    Why is Kafka used for building real-time data analytics?

    Enterprises widely use Kafka for developing real-time data pipelines as it can extract high-velocity high volume data . This high-velocity data is passed through a real-time pipeline of Kafka. The published data is subscribed using any streaming platforms like Spark or using any Kafka connectors like Node Rdkafka, Java Kafka connectors.

    Why do we still need Kafka?

    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.

    Why is Kafka so fast?

    Kafka can be very fast because it presents the log data structure as a first-class citizen. It’s not a traditional message broker with lots of bells and whistles. Kafka does not have individual message IDs. Messages are simply addressed by their offset in the log.

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