Apache Flink

Apache Flink is a framework and distributed processing engine designed for stateful computations over unbounded and bounded data streams. It is a versatile solution suitable for companies of all sizes, from small startups to large enterprises. According to the vendor, Apache Flink is utilized by a range of professionals and industries, including data engineers, data scientists, software engineers, IT professionals, and the financial services sector.

Key Features

Exactly-once state consistency: According to the vendor, Apache Flink provides exactly-once state consistency to eliminate duplicate or missing data issues.

Event-time processing: Apache Flink supports event-time processing, allowing users to handle data streams based on event timestamps for accurate processing of out-of-order events and delayed data.

Sophisticated late data handling: Flink offers mechanisms to handle late data in event streams, enabling users to define windowing strategies that accommodate late data arrivals.

Layered APIs: Apache Flink provides layered APIs, including SQL on both stream and batch data, DataStream API for low-level stream processing, and DataSet API for batch processing, offering flexibility and ease of use for developers.

SQL on Stream & Batch Data: Flink allows users to write SQL queries to process both streaming and batch data, leveraging SQL skills for data transformations, aggregations, and analytics.

DataStream API & DataSet API: Flink provides DataStream API for building low-level stream processing applications and DataSet API for batch processing, offering a rich set of operators and functions for data manipulation and complex computations.

ProcessFunction (Time & State): According to the vendor, Flink's ProcessFunction API allows developers to define custom functions for data stream processing based on time and state, providing fine-grained control over event processing and state management.

Flexible deployment: Apache Flink supports flexible deployment options, allowing users to run applications on various cluster environments such as standalone clusters, Apache Mesos, Apache Hadoop YARN, and Kubernetes, enabling seamless integration with existing infrastructure.

High-availability setup: Flink supports high-availability setups for fault tolerance and continuous operation of streaming applications, with mechanisms for automatic failover and recovery.

Savepoints: According to the vendor, Flink allows users to create savepoints, consistent snapshots of application state, for upgrades, debugging, or restoring the application state in case of failures.