Cloud Commute

Change Data Capture and Stream Processing in the Cloud - Gunnar Morling from Decodable

Apr 26, 2024

Gunnar Morling from Decodable shares insights on change data capture using Debezium and stream processing with Apache Flink. Topics cover real-time data analytics, seamless integration with data systems like Postgres and MySQL, and the importance of unified change event formats. Gunnar also discusses Java performance tests, Apache Flink for processing real-time data streams, and trends in database evolution and microservices.

23:24

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Episode guests

Gunnar Morling

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Episode notes

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Quick takeaways

Change data capture tools like Debezium extract modifications from databases for real-time analytics.

Apache Flink enables stream processing of bounded and unbounded event streams with varied APIs.

Deep dives

Gunnar's Background and Role at Decodable

Gunnar, a software engineer at Decodable, discusses his role at the startup focused on data streaming. He elaborates on his experience at Red Hat where he worked on various projects under the Hibernate umbrella, including bean validation and Debezium, a change data capture tool. Gunnar mentions his involvement in outreach activities such as blog posts, podcasts, and conferences.

Introduction

3min

Exploring Real-time Data Movement and Processing with a SaaS Stream Processing Service

2min

Java Performance Test Success

3min

Real-Time Data Processing with Apache Flink and DBZM Connectors

14min

Exploring Trends in Database Evolution and Microservices

2min

Gunnar Morling, from Decodable, a company simplifying the use of Apache Flink, talks about how to extract modifications from a database using change data capture tools, such as Debezium, and how to use Apache Flink or Decodable to run your real-time analytics or queries in a stream processing fashion.

If you have questions to Gunnar, you can reach him here: