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Last updated : Nov 20, 2019
NOT ON THE CURRENT EDITION
This blip is not on the current edition of the Radar. If it was on one of the last few editions, it is likely that it is still relevant. If the blip is older, it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar. Understand more
Nov 2019
Trial ?

Apache Flink ha visto una creciente adopción desde nuestra evaluación inicial en 2016. Flink es reconocido como el motor líder de procesamiento de flujos y también ha madurado gradualmente en los campos del procesamiento por lotes (batch) y del machine learning. Uno de los diferenciadores clave de Flink con respecto a otros motores de procesamiento de flujos es el uso de puntos de control consistentes del estado de una aplicación. En caso de fallo, la aplicación se reinicia y su estado se carga desde el último punto de control, de modo que la aplicación puede seguir procesando como si el fallo nunca hubiera ocurrido. Esto nos ayuda a reducir la complejidad de la construcción y operación de sistemas externos para la tolerancia a fallos. Vemos cada vez más empresas que utilizan Flink para construir su plataforma de procesamiento de datos.

Nov 2016
Assess ?

Interest continues to build for Apache Flink, a new-generation platform for scalable distributed batch and stream processing. At the core of Apache Flink is a streaming data-flow engine, with support for tabular (SQL-like), graph-processing and machine learning operations. Apache Flink stands out with feature rich capabilities for stream processing: event time, rich streaming window operations, fault tolerance and exactly-once semantics. The project shows significant ongoing activity, with the latest release (1.1) introducing new datasource/sink integrations as well as improved streaming features.

Apr 2016
Assess ?

Apache Flink is a new-generation platform for scalable distributed batch and stream processing. At its core is a streaming data-flow engine. It also supports tabular (SQL-like), graph-processing and machine-learning operations. Apache Flink stands out with feature-rich capabilities for stream processing: event time, rich streaming window operations, fault tolerance and exactly-once semantics. While it hasn't reached version 1.0, it has raised significant community interest due to innovations in stream processing, memory handling, state management and simplicity of configuration.

Published : Apr 05, 2016

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