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Confluent Unveils Apache Flink on Confluent Cloud, Making it Easier to Build Real-Time Applications with Stream Processing on a Unified Platform

Confluent launches the industry’s only serverless, cloud-native Flink service to simplify building high-quality, reusable data streams

Confluent expands Stream Governance capabilities with Data Portal, so teams can easily find all the real-time data streams in an organization

New Confluent Cloud Enterprise offering lowers the cost of private networking and storage for Apache Kafka

Confluent, the data streaming pioneer, announced the open preview of Apache Flink on Confluent Cloud, a fully managed service for stream processing that makes it easier for companies to filter, join, and enrich data streams with Flink. With data streams processed on the fly, organizations are able to react and innovate faster with timely insights. In addition, Confluent announced Data Portal to help teams discover all the real-time data streams within their organizations, Enterprise Clusters to cut Apache Kafka costs for serverless private networking, and reduced storage costs for Confluent Cloud.

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“Companies globally are leveraging data streaming with Apache Kafka to power real-time experiences”

Data streaming is a critical business requirement – 72% of IT leaders use it to power mission-critical systems, according to the 2023 Data Streaming report. But streaming data is only part of the puzzle. To derive the full value of data streams, organizations need to combine, enrich, and reshape those streams with other data from across their organization. In a data streaming platform, stream processing acts as the compute layer that turns data into valuable insights and action.

As one of the top projects of the Apache Software Foundation, Flink has emerged as the de facto standard for stream processing. Flink’s high performance, rich feature set, and robust developer community make it one of the most popular choices for large-scale, high throughput, and low-latency stream processing. Since Kafka has become the standard technology for data streaming, Flink is often used in tandem with Kafka to support companies’ mission-critical workloads.

“Companies globally are leveraging data streaming with Apache Kafka to power real-time experiences,” said Shaun Clowes, Chief Product Officer at Confluent. “While data streaming connects data across an organization, stream processing tools like Apache Flink make it possible to act on that data in real time and accelerate the development of new use cases. Our managed Kafka and Flink offerings are like the peanut butter and jelly of data streaming. They work better together on a unified platform to connect and enrich data so teams can uncover more insights and deliver impactful experiences that move the needle.”

Flink makes it possible for ride sharing companies to match drivers and riders, for banks to alert users on fraudulent activity, and for social media companies to offer personalized content recommendations.

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“Stream processing is critical for identifying and protecting against security risks in real time,” said Vinay Krishna Patnana, Engineering Manager at Cisco Meraki. “With Confluent’s fully managed Flink offering, we can access, aggregate, and enrich data from IoT sensors, smart cameras, and Wi-Fi analytics to swiftly take action on potential threats in real time, such as intrusion detection. This enables us to process sensor data as soon as the events occur, allowing for faster detection and response to security incidents without any added operational burden.”

However, like Kafka and other open source technologies, self-managing Flink is operationally complex, has a steep learning curve, and comes with expensive infrastructure and management costs.

Confluent’s Apache Flink service simplifies stream processing, enabling faster application development

Apache Flink on Confluent Cloud allows teams to create high-quality, reusable data streams that can be delivered anywhere in real time. With Confluent’s fully managed and elastically scalable Flink service, teams can reduce the architectural complexity and operational burdens of stream processing to enrich streaming data and power innovative use cases.

“Stream processing involves real-time integration and transformation of streams of event data, powering systems across industries ranging from fraud detection in finance to personalized recommendations in e-commerce,” said Matt Aslett, Vice President and Research Director at Ventana Research. “When used in combination, Apache Flink and Apache Kafka can enable data reusability and avoid redundant downstream processing. The delivery of Flink and Kafka as fully managed services delivers stream processing without the complexities of infrastructure management, enabling teams to focus on building real-time streaming applications and pipelines that differentiate the business.”

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