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WEBINAR: Change Stream Processing With Apache Flink

Decodable Team

In this demo-heavy webinar Gunnar Morling and Sharon Xie answer common questions on change stream processing:

- What is Change Data Capture (CDC) and why should I care?

- What do I gain when I integrate CDC with Apache Flink?

After this introduction, they switch to code to show how it works in a demo that includes CDC sources, stream processing and delivery to an Elastic database for searching.

Gunnar Morling, Former Project Lead For Debezium, Joins Decodable

Gunnar Morling, former project lead for Debezium, has joined Decodable's engineering team, boosting our open source and change data capture (CDC) capabilities. Gunnar brings a wealth of experience as a Java Champion and will also contribute to Decodable's work with Apache Flink and the open source developer community at large.

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Demo Day - Intro to Decodable and the new UX

Recorded from the Demo Day on March 10th 2022, Decodable CEO Eric Sammer demonstrates the capabilities of the real-time data engineering platform through the new user experience.

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Real Time Streaming Joins With SQL

Decodable enables continuous SQL joins across streaming sources including streaming systems like Kafka, Pulsar and Kinesis as well as databases with Change Data Capture (CDC). This is exactly the use-case for real-time joins. In this blog we'll explore how this works, and how it helps bring siloed data into play in low-latency streaming applications.

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Record Replay, for When You Want to Begin Again

Decodable has built upon the underlying capabilities of Flink to provide a platform that enables you to start a pipeline, pipeline preview, or connection from the earliest record available so that all records up to the current moment can be reprocessed. Essentially this gives you a “time machine” of sorts, allowing you to go backwards or forwards in time to the moment when you want to start processing records.

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