Snapshot queries, a new feature of Confluent Cloud for Apache Flink, combines batch and stream processing capabilities in one place.

On Confluent Cloud for Apache Flink®, snapshot queries combine batch and stream processing to enable AI apps and agents to act on past and present data

New private networking and security features make stream processing more secure and enterprise-ready

LONDON, May 20, 2025--(BUSINESS WIRE)--Confluent, Inc. (Nasdaq: CFLT), the data streaming pioneer, announced new Confluent Cloud capabilities that make it easier to process and secure data for faster insights and decision-making. Snapshot queries, new in Confluent Cloud for Apache Flink®, bring together real-time and historic data processing to make artificial intelligence (AI) agents and analytics smarter. Confluent Cloud network (CCN) routing simplifies private networking for Apache Flink®, and IP Filtering adds access controls for publicly accessible Flink pipelines, securing data for agentic AI and analytics.

"Agentic AI is moving from hype to enterprise adoption as organizations look to gain a competitive edge and win in today’s market," said Shaun Clowes, Chief Product Officer at Confluent. "But without high-quality data, even the most advanced systems can’t deliver real value. The new Confluent Cloud for Apache Flink® features make it possible to blend real-time and batch data so that enterprises can trust their agentic AI to drive real change."

Bridging the Real-Time and Batch Divide

"The rise of agentic AI orchestration is expected to accelerate, and companies need to start preparing now," said Stewart Bond, Vice President of Data Intelligence and Integration Software at IDC. "To unlock agentic AI’s full potential, companies should seek solutions that unify disparate data types, including structured, unstructured, real-time, and historical information, in a single environment. This allows AI to derive richer insights and drive more impactful outcomes."

Agentic AI is driving widespread change in business operations by increasing efficiency and powering faster decision-making by analyzing data to uncover valuable trends and insights. However, for AI agents to make the right decisions, they need historical context about what happened in the past and insight into what’s happening right now. For example, for fraud detection, banks need real-time data to react in the moment and historical data to see if a transaction fits a customer’s usual patterns. Hospitals need real-time vitals alongside patient medical history to make safe, informed treatment decisions. But to leverage both past and present data, teams often have to use separate tools and develop manual workarounds, resulting in time-consuming work and broken workflows. Additionally, it’s important to secure the data that’s used for analytics and agentic AI; this ensures trustworthy results and prevents sensitive data from being accessed.

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Snapshot Queries Unify Processing on One Platform

In Confluent Cloud, snapshot queries let teams unify historical and streaming data with a single product and language, enabling consistent, intelligent experiences for both analytics and agentic AI. With seamless Tableflow integration, teams can easily gain context from past data. Snapshot queries allow teams to explore, test, and analyze data without spinning up new workloads. This makes it easier to supply agents with context from historic and real-time data or conduct an audit to understand key trends and patterns. Snapshot queries are now available in early access.

CCN Routing Simplifies Private Networking for Flink

Private networking is important for organizations that require an additional layer of security. Confluent offers a streamlined private networking solution by reusing existing CCNs that teams have already created for Apache Kafka® clusters. Teams can use CCN to securely connect their data to any Flink workload, such as streaming pipelines, AI agents, or analytics. CCN routing is now generally available on Amazon Web Services (AWS) in all regions where Flink is supported.

IP Filtering Protects Flink Workloads in Hybrid Environments

Many organizations that operate in hybrid environments need more control over which data can be publicly accessed. IP Filtering for Flink helps teams restrict internet traffic to allowed IPs and improves visibility into unauthorized access attempts by making it easier to track the attempts. IP Filtering is generally available for all Confluent Cloud users.

Now organizations can more easily turn the promise of agentic AI into a competitive advantage. To learn more about the other new Confluent Cloud features, including the Snowflake source connector, cross-cloud Cluster Linking, and new Schema Registry private networking features, check out the launch blog.

Additional Resources

Start your free trial of Confluent Cloud. No credit card required. Ask our Professional Services experts for faster adoption. Check out the launch blog about additional Confluent Cloud features.

About Confluent

Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion—designed to be the intelligent connective tissue enabling real-time data from multiple sources to constantly stream across an organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital frontend customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io.

As our roadmap may change in the future, the features referred to here may change, may not be delivered on time, or may not be delivered at all. This information is not a commitment to deliver any functionality, and customers should make their purchasing decisions based on features that are currently available.

Confluent® and associated marks are trademarks or registered trademarks of Confluent, Inc.

Apache®, Apache Kafka®, Kafka®, Apache Flink®, and Flink® are registered trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by the use of these marks. All other trademarks are the property of their respective owners.

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