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.
May 11, 2024 · As we have found out, Kafka uses topic partitions to allow parallel message delivery and load balancing of consumers. But Kafka itself must be scalable and fault-tolerant. So we typically do not use a single Kafka Broker, but a Cluster of multiple brokers.
We build and test Apache Kafka with Java 8, 11, 17 and 21. We set the release parameter in javac and scalac to 8 to ensure the generated binaries are compatible with Java 8 or higher (independently of the Java version used for compilation).
The project aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds. Kafka can connect to external systems (for data import/export) via Kafka Connect, and provides the Kafka Streams libraries for stream processing applications.
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.
Kafka 1.1.0 includes a number of significant new features. Here is a summary of some notable changes: Kafka 1.1.0 includes significant improvements to the Kafka Controller that speed up controlled shutdown. ZooKeeper session expiration edge cases have also been fixed as part of this effort.
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.
Kafka is primarily used to build real-time streaming data pipelines and applications that adapt to the data streams. It combines messaging, storage, and stream processing to allow storage and analysis of both historical and real-time data.
Learn what Apache Kafka is, and how it works as a distributed data streaming platform for real-time data pipelines, integration, and stream processing. Discover Kafka’s use cases with examples.
