Kafka
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Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. Above is a snapshot of the number of top-ten largest companies using Kafka, per-industry.
Apache Kafka is a data streaming system used for real-time data pipelines, data integration, and event-driven systems. Learn how Kafka works with examples and use cases.
Apache Kafka also works with external stream processing systems such as Apache Apex, Apache Beam, Apache Flink, Apache Spark, Apache Storm, and Apache NiFi. Kafka runs on a cluster of one or more servers (called brokers), and the partitions of all topics are distributed across the cluster nodes.
Using Apache Kafka, developers may create robust stream-processing applications with the help of Kafka Streams. It offers APIs and a high-level Domain-Specific Language (DSL) for handling, converting, and evaluating continuous streams of data.
Apache Kafka is a distributed data streaming platform used for real-time data pipelines, integration, stream processing, and more. Learn how Kafka works and how it's used with examples.
Apache Kafka (Kafka) is an open-source, distributed streaming platform that enables (among other things) the development of real-time, event-driven applications and user experiences on the web. Today, billions of data sources continuously generate streams of data records, including streams of events. An event is a digital record of an action ...
To process streams of events as they occur or retrospectively. And all this functionality is provided in a distributed, highly scalable, elastic, fault-tolerant, and secure manner. Kafka can be deployed on bare-metal hardware, virtual machines, and containers, and on-premises as well as in the cloud.
At its core, Kafka is a distributed publish-subscribe messaging system. Data is written to Kafka topics by producers and consumed from those topics by consumers. Kafka topics can be partitioned, enabling the parallel processing of data, and topics can be replicated across multiple brokers for fault tolerance.
Building real-time streaming applications that transform or react to the streams of data. First a few concepts: Kafka is run as a cluster on one or more servers that can span multiple datacenters. The Kafka cluster stores streams of records in categories called topics.
Apache Kafka is a platform for collecting, processing, and storing streaming data. Kafka lets apps handle billions of streamed data points/minute.
