Explanation:
Apache Kafka is a distributed streaming framework for creating real-time data pipelines and applications that react to changing data streams.
Explanation:
The programming languages Java and Scala were used to create Kafka.
Explanation:
The maximum size of a message that can be received by the Kafka server is 1,000,000 bytes.
Explanation:
LinkedIn created Kafka in 2009, but it was eventually outsourced to the Apache Software Foundation in 2011. In a word, Kafka is a distributed streaming technology with high volume, high throughput, super scalability, and reliability.
Explanation:
In any case, Kafka ensures that no data is lost.
Explanation:
A Kafka server functions similarly to this messaging system. The Kafka server, on the other hand, is utilized as a message broker. A producer and a consumer are the two basic abstractions of a Kafka server. Content is created by producers and then published to the Kafka server. This content is consumed from the Kafka server by a consumer. In this example, each producer can generate and submit messages to a Kafka server. These messages can then be consumed straight from the Kafka server by a consumer. In this way, Kafka serves as a go-between for the two.
Explanation:
The traditional message transfer method includes two methods: queuing and delivery. Queuing is a method in which a group of consumers read a message from the server, and each message is delivered to one of them. Publish-Subscribe: In Publish-Subscribe, messages are published to all consumers.
Explanation:
Zookeeper is a top-tier cluster coordination service that employs the most reliable synchronization techniques to keep the cluster's nodes perfectly connected. Apache Zookeeper solves distributed environment management with its simple architecture and API.
Explanation:
Queuing is a method in which a group of consumers read a message from the server, and each message is delivered to one of them.
