Unifying Batch and Stream Processing with Serverless Flink

Explore the latest innovations from the Q2 Confluent Cloud launch

The Confluent Cloud Q1 ’25 launch introduces powerful new capabilities to unify batch and stream processing, combining your real-time streams with rich historical context to power AI and analytics workloads.

Join us to see Flink Snapshot Queries in action and explore how Confluent Cloud for Apache Flink® brings together streaming and batch processing. With our serverless Flink product, you can now query historical and real-time data using the same SQL interface—no need to stitch together separate systems or rewrite logic. Snapshot Queries is also seamlessly integrated with Tableflow, enabling Flink to automatically read from open table formats to unlock deep analytics and conduct historical audits. Flink’s unified approach enables deeper insights and a more streamlined path to building AI-driven applications that rely on both fresh and long-term context.

You’ll also learn about several features to simplify private networking, including AWS PrivateLink for Schema Registry as well as IP Filtering and CCN routing support. Plus, we’ll dive into cross-cloud Cluster Linking and several new connectors.

In this demo webinar with Q&A, learn about our latest product updates through the lens of an agentic AI use case. You’ll learn how to:

• Convert Kafka topics and schemas to open table formats like Delta in just a few clicks with Tableflow to feed analytical engines running on platforms like Databricks
• Run point-in-time Flink SQL queries on bounded Kafka and Tableflow data with Flink Snapshot Queries to conduct ad-hoc analyses, analyze historical trends, and debug pipelines.

Get all the details on the new Confluent Cloud features in the Q2 ʼ25 announcement blog.

Ready to explore these new features? Get started for free with Confluent Cloud and receive $400 to spend within your first 30 days.