Apache Kafka FAQs
Apache Kafka is a popular distributed platform for event streaming and building high-performance data pipelines. Kafka is open-source, and is used by thousands of companies for data streaming and analytics, data integration, and other data-driven applications.
Some of the key features of Apache Kafka include seamless scalability, integration with hundreds of event sources, high performance and throughput, as well as support for a large ecosystem of community-driven tools.
If building real-time data pipelines and streaming applications is your goal, then Apache Kafka is a must-have tool in your data stack.
Frequently Asked Questions
What is Apache Kafka used for?
Apache Kafka is a event messaging service that enables developers to build and operate various kinds of data streams.
Is it hard to set up Apache Kafka?
Difficulty can vary based on your existing tech stack and data streaming needs. Many users choose to simplify implementation by sending data to Apache Kafka through secure event messaging integration tools like RudderStack.
How much does it cost to integrate Apache Kafka with RudderStack?
How Does Apache Kafka work?
Apache Kafka is an open-source publish-subscribe messaging system that enables you to build scalable, fault-tolerant distributed applications with ease. The core architecture of Apache Kafka revolves around three major components - publishers, subscribers, and topics. You can also enable parallel processing and consumption of data by partitioning the topics. All the messages sent to Kafka are persisted and replicated to peer brokers. You can also configure the time period for which these messages are persisted.
Why Is Apache Kafka so popular?
Apache Kafka is used by thousands of companies worldwide for building high performance data pipelines and distributed applications at scale. Many companies use Apache Kafka in their technology stack for various other use-cases such as streaming analytics, data integration and building data-intensive applications. Apache Kafka is popular and widely-used for the following reasons: - It offers low latency and high throughput when it comes to delivering messages. This feature comes in handy in the Big Data space where ingesting and moving large amounts of data quickly and reliably is a critical requirement. - Kafka scales very well, allowing you to work with large data workloads with ease. - It integrates seamlessly with hundreds of event sources such as PostgreSQL, Elasticsearch, Amazon S3, and more. - As Kafka is an open-source project, there is a strong and vibrant community of users who are involved in continuously improving it. Kafka also supports a large ecosystem of other open-source tools.