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Category: Kafka / Flink

Exposing Kafka Data in Iceberg using Tableflow

Published 2024-03-20 by Kevin Feasel

Marc Selwan announces a new product:

We’re excited to talk about our vision for Tableflow, which makes it push-button simple to take Apache Kafka® data and feed it directly into your data lake, warehouse, or analytics engine as Apache Iceberg® tables. Making operational data accessible to the analytical world is traditionally a complex, expensive, and brittle process and we believe we can do better to unify the operational and analytical estates.

Tableflow removes all this erroneous, duplicative work and helps convert Kafka topics and associated schemas to Iceberg tables in one click. This is central to our Confluent’s vision to build the world’s leading data streaming platform that fuels any operational and analytical workload with real-time data products. 

It looks like this is currently in early access, but you can see where Confluent intends to take the product.

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Apache Kafka 3.7 Released

Published 2024-02-28 by Kevin Feasel

Stanislav Kozlovski makes an announcement:

We are proud to announce the release of Apache Kafka® 3.7.0. This release contains many new features and improvements. This blog post will highlight some of the more prominent features. For a full list of changes, be sure to check the release notes.

See the Upgrading to 3.7.0 from any version 0.8.x through 3.6.x section in the documentation for the list of notable changes and detailed upgrade steps.

Read on to see what’s new. Looks like they’ve taken care of a couple dozen items in this release, so plenty to read there.

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Combining Kafka and Flink

Published 2024-02-20 by Kevin Feasel

Gautam Goswami shares some thoughts:

In short, the process of collecting data in real-time as streams of events from event sources such as databases, sensors, and software applications is known as event streaming. With real-time data processing and analytics in mind, Apache Flink is a potent open-source program. For situations where quick insights and minimal processing latency are critical, it offers a consistent and effective platform for managing continuous streams of data. 

I’ve found it interesting that Confluent people have spent a lot of time the past several months talking up Apache Flink and Kafka+Flink combinations.

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