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The data Artisans Blog

Apache Flink, stream processing, event-driven applications, and more.

Category: Resources

Savepoints, Part 2: Streaming Applications in the Pit Lane

By Fabian Hueske (@fhueske) and Mike Winters (@wints) Last month, we gave a high-level overview of Apache Flink® savepoints and touched on why and how you’d reprocess data in a streaming applicatio...

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Savepoints: Turning Back Time

This post is the first in a series where the data Artisans team will highlight some of Apache Flink’s® core features. By Fabian Hueske (@fhueske) and Mike Winters (@wints) Stream processing is comm...

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Apache Flink and Apache Kafka Streams

This blog post is written jointly by Stephan Ewen, CTO of data Artisans, and Neha Narkhede, CTO of Confluent. You can also find this post at the Confluent blog. The open source stream processing space...

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Robust Stream Processing with Apache Flink®: A Simple Walkthrough

Jamie Grier, Director of Applications Engineering at data Artisans, gave an in-depth Apache Flink® demonstration at OSCON 2016 in Austin, TX. A recording is available on YouTube if you’d like to se...

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RBEA: Scalable Real-Time Analytics at King

This is a guest blog post written by Gyula Fóra and Mattias Andersson from The original post can be found on the King Tech Blog. This blogpost introduces RBEA (Rule-Based Event Aggregator),...

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Extending the Yahoo! Streaming Benchmark

Update December 18, 2017: Nearly 2 years after this initial post, we discussed the Yahoo streaming benchmark in another blog post where we cover some of the issues we see with modern benchmarking met...

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How Apache Flink™ Enables New Streaming Applications, Part 1

(For the rest of this series, see part 2 here and part 3 here)Stream data processing is booming in popularity, as it promises better insights from fresher data, as well as a radically simplified pipe...

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How we selected Apache Flink™ as our Stream Processing Framework at the Otto Group Business Intelligence Department

This is a guest post written by Christian Kreutzfeldt (@mnxfst) and Alexander Kolb (@lofifnc) from the Otto Group Business Intelligence Department....

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Kafka + Flink: A Practical, How-To Guide

A very common use case for Apache Flink™ is stream data movement and analytics. More often than not, the data streams are ingested from Apache Kafka, a system that provides durability and pub/sub fu...

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High-throughput, low-latency, and exactly-once stream processing with Apache Flink™

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...

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