Confluent, the data streaming pioneer, announced the general availability of Confluent Cloud for Apache Flink, a fully managed service for Apache Flink® that enables customers to process data in real time and create high-quality, reusable data streams. Confluent Cloud for Apache Flink® is available across AWS, GoogleCloud and MSAzure . Backed by Confluent’s 99.99% uptime SLA, Confluent’s cloud-native service for Flink enables reliable, serverless stream processing.
Organizations are under incredible pressure to deliver exceptional customer experiences and streamline operations with cutting-edge use cases like fraud detection, predictive maintenance, and real-time inventory and supply chain management. Stream processing is a critical part of bringing these real-time experiences to life because it enables organizations to act on data as it arrives rather than waiting to process it in batches when the data is often already stale and out of date.
As the compute layer in the data streaming infrastructure, stream processing helps teams filter, join, and enrich data in real time to make it more usable and valuable for sharing with downstream applications and systems. It creates high-quality data streams that can be reused for multiple projects and provides improved agility, data consistency, and cost savings compared to traditional batch processing solutions. As the de facto stream processing standard, Fink is relied upon by innovative companies like Airbnb, Uber, Netflix, and Stripe to support mission-critical streaming workloads. That is what sparked the surge in Flink’s popularity. In 2023, Flink was downloaded almost 1 million times.
"Stream processing is essential for extracting timely insights from continuous data streams to power a wide range of critical use cases including fraud detection, dynamic pricing, and real-time inventory and supply chain management,” said Stewart Bond, research VP, data integration and data intelligence software at IDC. “Apache Flink is becoming a prominent stream processing framework in this shift towards real-time insights. Flink and Apache Kafka® are commonly used together for real-time data processing, but differing data formats and inconsistent schemas can cause integration challenges and hinder the quality of streaming data for downstream systems and consumers. A fully managed, unified Kafka and Flink platform with integrated monitoring, security, and governance capabilities can provide organizations with a seamless and efficient way to ensure high-quality and consistent data streams to fuel real-time applications and use cases, while reducing operational burdens and costs.”
As a leading cloud-native, serverless Flink offering, Confluent Cloud for Apache Flink® enables customers to easily build high-quality, reusable data streams to power all of their real-time applications and analytics needs.
“Stream processing allows organizations to transform raw streams of data into powerful insights,” said Shaun Clowes, chief product officer at Confluent. “Flink’s high performance, low latency, and strong community make it the best choice for developers to use for stream processing. With Kafka and Flink fully integrated in a unified platform, Confluent removes the technical barriers and provides the necessary tools so organizations can focus on innovating instead of infrastructure management.”
"To meet rising customer demands in a volatile energy market, we need to deliver near real-time data to our client-facing applications,” said Sami AlAshabi, solutions architect at Essent. “Relying on batch processing can cause performance issues and result in poor decision-making based on outdated data. By using Kafka and Flink together in a unified platform, our teams will be able to easily build intelligent streaming data pipelines that can extract data from various sources, process it in real time, and feed it to our downstream consumers for timely analysis without any operational challenges. We’re excited about Confluent’s fully managed Flink service, because it will help make stream processing accessible to everyone by creating high quality, reusable data streams to fuel innovation and data exploration across our lines of business.”