自从Apache Flink在2016年首次进入技术雷达“评估”环以来，越来越多的人开始采用它了。Flink被视为领先的流处理引擎，在批处理与机器学习领域也逐渐成熟。与其他流处理引擎相比，Flink的独特之处在于，它使用了一致的应用状态检查点。当发生错误时，应用可以重启，并从最近的检查点载入状态继续处理，就好像错误从未发生一样，这让我们不必为了容错而不得不构建和操作复杂的外部系统。我们看到越来越多的公司，在使用Flink构建他们的数据处理平台。
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.
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.
