Confluent Unites Batch and Stream Processing for Faster, Smarter Agentic AI and Analytics
On Confluent Cloud for Apache Flink庐, 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
Snapshot queries, a new feature of Confluent Cloud for Apache Flink, combines batch and stream processing capabilities in one place.
鈥淎gentic AI is moving from hype to enterprise adoption as organizations look to gain a competitive edge and win in today鈥檚 market,鈥� said Shaun Clowes, Chief Product Officer at Confluent. 鈥淏ut without high-quality data, even the most advanced systems can鈥檛 deliver real value. The new Confluent Cloud for Apache Flink庐 features make it possible to blend real-time and batch data so that enterprises can trust their agentic AI to drive real change.鈥�
Bridging the AG真人官方-Time and Batch Divide
鈥淭he rise of agentic AI orchestration is expected to accelerate, and companies need to start preparing now,鈥� said Stewart Bond, Vice President of Data Intelligence and Integration Software at IDC. 鈥淭o unlock agentic AI鈥檚 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.鈥�
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鈥檚 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鈥檚 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鈥檚 important to secure the data that鈥檚 used for analytics and agentic AI; this ensures trustworthy results and prevents sensitive data from being accessed.
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 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 .
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 that teams have already created for Apache Kafka庐 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. 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 .
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About Confluent
Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent鈥檚 cloud-native offering is the foundational platform for data in motion鈥攄esigned 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 .
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庐 and associated marks are trademarks or registered trademarks of Confluent, Inc.
Apache庐, Apache Kafka庐, Kafka庐, Apache Flink庐, and Flink庐 are registered trademarks of the Apache Software Foundation in
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Source: Confluent, Inc.
