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Schema Evolution in 6 Mins, Apache Kafka® 3.7, & Apache Flink® 1.19

March 21, 2024

Kafka Summit London (KSL) finished up just yesterday! We celebrated KIP-1000 and revisited the idea of a data product and how Kora Engine contributes to it. We’re excited to share the recorded sessions once they’re posted. In the meantime, you can view the talks from KSL 2023 and Current 2023.

If you weren’t able to attend, no worries, we’ve been releasing new and exciting content all the while. Check out the videos, blogs, and code resources below.

Apache Kafka® Resources:

  • Apache Kafka 3.7 has been released! Catch up on all the design updates with Danica Fine’s summary video or the announcement blog post from the release manager Stanislav Koslovski.
  • Event-driven architecture… hold on, what exactly is it? Get the low-down on the fundamentals from Adam Bellemare.
  • What is a producer? What is a consumer? Review the basics with these two clarifying videos from Dan Weston.
  • Take a look at the Avro-to-xml mapper from Michelin that you may find useful if you use Avro for Schema Registry.
  • Schemas are a data contract between teams… but what happens when that contract needs to change? Watch Wade Waldron’s video schema evolution in 6 minutes.
  • Learn how to perform change data capture (CDC) for MySQL tables using Flink in this practical blog post from Sai Kondapalli.
  • Tejas Kumar tackles event sourcing for the rest of us with this GitHub sample of a KafkaJS project.

Apache Flink® Resources:

A Droplet from Stack Overflow:

David Anderson explains the difference between task slot and parallelism in Apache Flink.

Got your own favorite Stack Overflow answer related to Flink or Kafka? Send it in to!

Terminal Tip of the Week:

What’s the difference between Data Definition Language (DDL), Data Manipulation Language (DML), and Data Query Language (DQL)? Let’s take a look at some examples:

DDL statements are imperative verbs that define metadata in FlinkSQL by adding, changing, or deleting tables. For example:

-- Modify the default watermark Add a column to the existing table
ALTER TABLE [catalog_name].[db_name].[table_name] MODIFY WATERMARK FOR
column-name1 AS column-name1;

DML statements are declarative verbs that read and modify data in Flink tables, like this:

INSERT INTO orders VALUES (1, 1001, '2023-02-24', 50.0);

DQL statements select data from a Flink table:

SELECT * FROM orders;

Links from Around the Web:

Upcoming Events:


  • Current 2024 (Sep 17-18): The call for papers for Current 2024 is now closed. Thank you for your submissions! We will keep you updated on speaker and agenda announcements as they become available.
  • Kafka Summit Bangalore (May 2): Registration for KSB is now open! While we wait for the first-ever Kafka Summit in Bangalore, you can check out the agenda and speakers for the event.


By the way…

We hope you enjoyed our curated assortment of resources! If you’d like to provide feedback, suggest ideas for content you’d like to see, or you want to submit your own resource for consideration, email us at!

If you’d like to view previous editions of the newsletter, visit our archive.

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P.S. If you want to learn more about Kafka, Flink, or Confluent Cloud, visit our developer site at Confluent Developer.

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