The data Artisans Blog
Apache Flink, stream processing, event-driven applications, and more.
Category: Flink Features
How Apache Flink™ handles backpressureAugust 31, 2015
People often ask us how Flink deals with backpressure effects. The answer is simple: Flink does not use any sophisticated mechanism, because it does not need one. It gracefully responds to backpressur...
High-throughput, low-latency, and exactly-once stream processing with Apache Flink™August 5, 2015
The popularity of stream data platforms is skyrocketing. Several companies are transitioning parts of their data infrastructure to a streaming paradigm as a solution to increasing demands for real-tim...
Real-time stream processing: The next step for Apache Flink™May 6, 2015
This post also appears as a guest post at the Confluent blog. Stream processing is becoming very popular with open source projects like Apache Kafka, Apache Samza, Apache Storm, Apache Spark’s Stre...
Announcing Google Cloud Dataflow on Flink and easy Flink deployment on Google CloudApril 5, 2015
Today, we are pleased to announce a deeper engagement between Google, data Artisans, and the broader Apache Flink™ community to bring easy Flink deployment to Google Cloud Platform, and enable Googl...
Data Analysis with Flink: A case study and tutorialNovember 29, 2014
This article is a step-by-step guide to implement a fairly sophisticated data analysis algorithm, end-to-end in Apache Flink. We will use the PageRankalgorithm, an algorithm used for ranking entities ...