Overview
Apache Flink is a distributed processing engine for stateful computations over data streams, positioned as the industry standard for high-throughput, low-latency streaming in 2026. Unlike batch-oriented frameworks, Flink treats batch processing as a special case of streaming, utilizing a unified execution model. Its architecture is built on the concept of 'Streams' and 'Transformations,' allowing for complex event-driven applications that maintain local state with high availability. By 2026, Flink has solidified its role in the AI stack through Flink ML and advanced integration with vector databases, enabling real-time feature engineering and online model inference. Its core strengths lie in its exactly-once processing guarantees, sophisticated windowing semantics, and robust fault tolerance via distributed snapshots (checkpoints). As enterprises move toward 'Real-time Everything,' Flink serves as the backbone for operational analytics, fraud detection, and dynamic pricing engines. The ecosystem has evolved significantly with the adoption of Flink SQL, making stream processing accessible to data analysts, while the Flink Kubernetes Operator has simplified cloud-native deployments across hybrid and multi-cloud environments.