{"id":31262,"date":"2022-12-30T06:00:00","date_gmt":"2022-12-30T14:00:00","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=31262"},"modified":"2022-12-27T17:08:36","modified_gmt":"2022-12-28T01:08:36","slug":"video-highlights-change-data-capture-with-apache-flink","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2022\/12\/30\/video-highlights-change-data-capture-with-apache-flink\/","title":{"rendered":"Video Highlights: Change Data Capture With Apache Flink"},"content":{"rendered":"\n

There is a growing role Change Data Capture<\/em> (CDC) plays in real-time data analytics (specifically, stream processing with open source tools like Debezium and Apache Flink). CDC lets users analyze data as it\u2019s generated by leveraging streaming from systems like Apache Kafka, Amazon Kinesis, and Azure Events Hubs to track and transport changes from one data system to another. With\u00a0CDC,\u00a0as records change in a source database, a stream of those changes is sent downstream to the destination database for analysis in real time. This is in contrast to systems that use batch processing, which can’t handle real-time demands efficiently.<\/p>\n\n\n\n

The featured video resource provided by Decodable<\/a> is a webinar in which CDC experts provide an overview of CDC with Flink and Debezium. It features 1) Gunnar Morling, one of the creators of the Debezium project and a Java Champion; 2) Jark Wu, a PMC member and Committer\u00a0at the Apache Flink project and\u00a0 creator of the Flink CDC project; and 3) Leonard Xu, committer of Flink SQL and leader of the Flink CDC project since 2021. <\/p>\n\n\n\n

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