Apache Kafka is a free and open-source distributed streaming platform which is capable of handling trillions of events a day. Kafka is used for building real-time data pipelines and streaming apps. It is an integral part of an ecosystem which is used for data processing, analytics, and machine learning.
What is Apache Kafka in simple terms?
Apache Kafka is a distributed streaming platform. It is used for building real-time data pipelines and streaming apps. It is a fast, scalable, and durable messaging system. Kafka is used in use cases where high throughput, low latency, and guaranteed order are required.
Kafka has a publish-subscribe messaging system. Kafka messages are persisted on disk and replicated within the cluster to prevent data loss. Kafka is designed to handle large streams of data.
Kafka is written in Scala and runs on the Java Virtual Machine (JVM).
Why is Apache Kafka so popular?
Apache Kafka is a popular open-source messaging system that is widely used in the industry today. There are many reasons for its popularity, but some of the most important ones include its high performance, its ability to handle large amounts of data, its reliability, and its easy-to-use APIs. Is Apache Kafka a database? No, Apache Kafka is not a database. It is a distributed streaming platform that enables you to build streaming applications that consume, process, and produce streams of data.
Why does Netflix use Kafka?
Netflix uses Kafka for two main reasons:
1) Kafka is highly scalable and can handle a large number of messages. This is important for Netflix because they need to be able to handle a large number of users streaming videos simultaneously.
2) Kafka is very fast and can process messages quickly. This is important for Netflix because they need to be able to deliver videos to users in real-time without any delays. Is Kafka an ETL tool? No, Apache Kafka is not an ETL tool. It is a distributed streaming platform that enables you to build applications that process, analyze, and publish streams of records in real time.