Ins & Outs of Using Kafka for Data Streaming

The Do’s & the Don’ts, the Ins & the Outs: Using Kafka for Data Streaming

If you’re interested in taking on Kafka for your use cases, Syncsort’s integration with the Kafka distributed messaging system allows users to leverage the easy-to-use graphical interface of its data integration solution, DMX-h to subscribe, transform and enrich enterprise-wide data coming from real-time Kafka queues.

DMX-h can also publish these enriched datasets to Kafka to simplify the creation of real-time analytical applications by cleansing, pre-processing and transforming data in motion.

Big Data Stack

Apache Kafka joins an already crowded Hadoop ecosystem, but enterprises are making room for it, because it is truly capable of handling data streams in real time.

In fact, for the last couple of years, Syncsort has focused on integrating DMX-h with both Apache Kafka and Apache Spark to address key customer use cases, allowing users to take advantage of two of the most powerful big data open source projects for large-scale, real-time data processing and analytics. This is part of their overall strategy for accessing and integrating data from enterprise-wide data sources, including mainframe, to support Big Data initiatives.

For more information, watch the video: “Real Time Streaming with Kafka and Syncsort DMX-h

Christy Wilson

Authored by Christy Wilson

Syncsort contributor Christy Wilson began writing for the technology sector in 2011, and has published hundreds of articles related to cloud computing, big data analysis, and related tech topics. Her passion is seeing the fruits of big data analysis realized in practical solutions that benefit businesses, consumers, and society as a whole.
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