Systems | Development | Analytics | API | Testing

Tableflow represents Kafka topics and associate schemas as open-table formats such as Apache Iceberg(Generally Available) or Delta Lake (Early Access) in a few clicks to feed any data lake, warehouse, or analytics engine. It removes the need for complex, costly and error-prone data pipelines that are currently being used to feed streaming data to data lakes while delivering strong read performance and automated data maintenance. Customers can also bring their own storage ensuring flexibility, cost savings, and security.

Chris Kapp of Henry Schein One shares how his team is securing HIPAA data through a smart naming strategy, internal governance, and tight control over tagging and access.

Despite its value, legacy data can feel like a roadblock in a fast-paced digital world—Henry Schein One is clearing the path forward with real-time data streaming. In this episode, Chris Kapp, Software Architect at Henry Schein One (HS1), shares how his team modernizes data management to stay competitive and unlock real-time insights. You’ll learn about: Get ready to future-proof your data strategy with this must-listen episode for technology leaders facing scalability, governance, or integration challenges.

Was the ELT bandwagon a mistake? Mike Agnich, General Manager, Data Streaming Platform at Confluent talks about why real-time ETL saves you from expensive headaches.

Data contracts aren't just a buzzword—David Araujo, Director of Product Management at Confluent, explains they’ve been hiding in Apache Kafka all along.

In the final episode of our 3-part series on the basics of data streaming, we take a deep dive into data integration—covering everything from data governance to data quality. Our guests, Mike Agnich, General Manager of Data Streaming Platform, and David Araujo, Director of Product Management at Confluent, explain why connectors are must-haves for integrating systems.

Flink’s secret weapon? Abhishek Walia, Staff Customer Success Technical Architect at Confluent, says it’s flexibility—whether you’re a developer, data scientist, or DBA.

We’re diving even deeper into the fundamentals of data streaming to explore stream processing—what it is, the best tools and frameworks, and its real-world applications. Our guests, Anna McDonald, Distinguished Technical Voice of the Customer at Confluent, and Abhishek Walia, Staff Customer Success Technical Architect at Confluent, break down what stream processing is, how it differs from batch processing, and why tools like Flink are game changers.

How do you build systems that keep up with a nonstop flood of data? Anna McDonald, Distinguished Technical Voice of the Customer at Confluent, explains how.

Finding pain is key to starting your real-time data streaming journey, as Tim Berglund, VP of Developer Relations at Confluent, shares.