The Howdy Glossary

Apache Flink is a highly performant data processing framework designed for distributed environments, supporting both batch and real-time streaming processing. It excels in event-time processing and state management within its streaming-first architecture, making it suitable for complex computations on unbounded and bounded data streams. Flink's versatility extends to providing APIs in Java and Scala, as well as an SQL interface (Flink SQL) for querying data streams and batch sources.

Originally developed by the Berlin-based company data Artisans, which later became Ververica, Apache Flink has evolved into a collaborative open-source project under the Apache Software Foundation. The framework was created by engineers at data Artisans, including some of its original creators, and has since garnered contributions from various organizations worldwide. This collaboration has helped Apache Flink develop into a robust tool that serves diverse high-performance analytics needs.

Apache Flink distinguishes itself with features like accurate event-time handling, efficient state management for fault tolerance, and seamless integration of batch and streaming tasks within one framework. These capabilities make it stand out against competitors such as Apache Spark, Storm, Kafka, Hadoop, and Google Dataflow. Its ability to maintain accurate analytics results despite delayed events through its unique design ensures reliable real-time insights for time-sensitive applications. Additionally, the flexibility offered through multiple programming languages (Java and Scala) and an SQL interface makes it accessible to users with varied technical expertise levels in fields like data engineering, science, and software development.