By integrating RudderStack with Apache Kafka, you can dump your event data from a variety of your data sources. The integration is quite simple too - all you need to do is specify the host name and topic name in the connection settings of the RudderStack dashboard. Once the destination is configured and enabled, all the events from your data sources will automatically start flowing to RudderStack, and can be routed to the specific Kafka topic in real-time.
By Adding Kafka Support for RudderStack, you can:
- Send your event data across different customer touch-points to Apache Kafka securely
- Dump your customer event data to the specified Kafka topic in real-time
- Skip any manual configuration or installing additional code snippets to send your event data to Kafka
Apache Kafka is a event messaging service that enables developers to build and operate various kinds of data streams.
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.
Pricing for Apache Kafka can vary depending on your use case and data volume. RudderStack offers transparent, volume-based event pricing. See RudderStack's pricing.
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.
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.
Apache Kafka is a popular distributed streaming platform. It allows you to handle large-scale workloads with high throughput and low latency. Apache Kafka is highly available and is used across the world for building real-time data pipelines and streaming applications.