STRIIM BLOG

Kafka to HDFS

Katherine Rincon
April 11, 2019 · 2 minute read

The real-time integration of messaging data from Kafka to HDFS augments transactional data for richer context. This allows organizations to gain optimal value from their analytics solutions and achieve a deeper understanding of operations – essential to establishing and sustaining competitive advantage.Kafka to HDFS

To truly leverage the high volumes of data residing in Kafka stores, companies need to be able move it, process it, and deliver it to a variety of on-premises and cloud systems with sub-second latency. It also needs to be integrated with operational data from a wide variety of sources.

Traditional batch-based solutions are not designed for situations where data is time-sensitive – they are simply too slow. To allow organizations use their data to enhance operations, tailor services, and improve customer experiences, data delivery from Kafka to HDFS systems needs to be scalable and in real time.

With Striim, companies can continuously deliver data in real time from Kafka to HDFS, as well as to a wide range of targets including Hadoop and cloud environments. Depending on the requirements of the organization, all the Kafka data can be written to a number of different targets simultaneously. In use cases where not all the data is required, data can be matched to specific criteria to deliver a highly relevant subset of data to the target.

Striim can create data flows to deliver the data from Kafka to HDFS in milliseconds, “as-is.” However, depending on how the data is going to be utilized, the user may require the data to be processed, prepared, and delivered in the right format. Striim supports continuous queries to filter, transform, aggregate, enrich, and analyze the data in-flight before delivering it with sub-second latency.

By analyzing the data in-flight, Kafka users can capture time-sensitive information as the data is flowing through the data stream. Striim pushes insights and alerts to interactive dashboards highlighting real-time data and the results of pattern matching, correlation, outlier detection, predictive analytics, and further enables drill-down and in-page filtering.

Learn more about integrating and processing Kafka to HDFS in real-time, please visit our Kafka integration page.

Our experts can show you how to get maximum value from your analytics solutions using Striim for real-time data integration from Kafka to HDFS. Please contact us to schedule a demo.

See how streaming data integration can work for you.

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