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Simple, Serverless Stream Processing
Easily build high-quality, reusable data streams with the industry’s only serverless Apache Flink® service, fully integrated with Apache Kafka® on Confluent Cloud across all three major clouds.
Confluent Platform for Apache Flink® is also now generally available for on-prem and private cloud workloads – see details here.
Real-time Use Cases Need Real-time Processing
Enable real-time data handling by transforming, analyzing and acting on data as it flows across your enterprise:
- Shift Left Data Pipelines: Clean and shape data as it's created, delivering fresh, reliable and reusable data to your data warehouse or data lake.
- Real-Time Materialized Views: Keep downstream systems and applications in sync with incrementally updated real-time universal data products.
- Classical Event Processing: Capture and process events as they occur, aggregating and analyzing them over time to detect trends, patterns and anomalies.
Unify Stream Processing and AI
Simplify development by bringing AI directly to your data streams. With Flink SQL and familiar APIs, you can build everything from real-time ML models to sophisticated, event-driven streaming agents that observe, reason, and act on the freshest business context —all on a unified, production-ready platform.
AI Model Inference
Call any LLM for inference directly within stream processing jobs using familiar Flink SQL.
Real-time Embeddings
Generate vector embeddings for RAG in real time, from any model to any vector database, across any cloud platform
Built-in ML Functions
Use out-of-the-box Flink SQL functions for powerful, low-code anomaly detection and forecasting.
Streaming Agents
Go beyond models to build production-ready, event-driven agents that act on real-time business events, with native Flink support for orchestration, tool calling, and replayability.
Filter. Join. Enrich.
Effortlessly filter, join, and enrich your data streams with Flink, the de facto standard for stream processing.
Real-time Processing
Power low-latency applications and pipelines that react to real-time events and provide timely insights
Data Reusability
Share consistent and reusable data streams widely with downstream applications and systems
Data Enrichment
Curate, filter, and augment data on-the-fly with additional context to improve completeness, accuracy, and compliance
Efficiency
Improve resource utilization and cost-effectiveness by avoiding redundant processing across silos
Cloud-native Experience
Enable high-performance and efficient stream processing at any scale, without the complexities of infrastructure management.
Fully Managed
Easily develop Flink applications with a serverless, SaaS-based experience instantly available and without ops burden
Elastic Scalability
Automatically scale up or down to meet the demands of the most complex workloads without overprovisioning
Infrastructure-as-code
Automate Flink deployment on Kubernetes for private cloud and on-prem workloads
Continuous Updates
Build using always up-to-date platform with automated upgrades
Kafka + Flink, Unified
Experience Kafka and Flink, unified as a complete enterprise-grade data streaming platform.
Enterprise-grade Security
Secure stream processing with built-in identity and access management, RBAC, and detailed audit logs
Stream Governance
Define and enforce universal data standards that enable scalable data compatibility
Monitoring
Ensure Flink applications run reliably, efficiently, and are easy to maintain
Connectors
Connect to and from any app and system with 120+ pre-built connectors
