How Apache Kafka Powers Real-Time Data Pipelines
Apache Kafka is an open-source platform designed for real-time data streaming, allowing continuous data flow from sources to destinations. It operates as a distributed system with brokers that manage data storage and message serving. Kafka's architecture supports scalability and efficiency, making it suitable for applications that require immediate data processing, such as real-time weather data pipelines.
- ▪Apache Kafka enables real-time data streaming, contrasting with traditional scheduled batch processing.
- ▪It consists of brokers that work together in clusters to ensure data reliability and availability.
- ▪Kafka topics allow data to be pushed and processed in parallel, enhancing throughput and scalability.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3190513) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Cliffe Okoth Posted on May 18 How Apache Kafka Powers Real-Time Data Pipelines #eventdriven #kafka #ai #dataengineering Most standard data pipelines run on a schedule. You use tools like Airflow and dbt to extract and transform large batches of API data once a day. However, what would happen if the data wasn't collected but rather is being collected in the moment.
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