The Future of ETL Isn’t What It Used To Be
In his book Design Patterns Explained, Alan Shalloway compares his car to an umbrella. After all, he uses both to stay dry in the rain. The umbrella has an advantage […]
In his book Design Patterns Explained, Alan Shalloway compares his car to an umbrella. After all, he uses both to stay dry in the rain. The umbrella has an advantage […]
Introduction What’s great about the Kafka Streams API is not just how fast your application can process data with it, but also how fast you can get up and running […]
This post was co-written with Michael Noll, Product Manager, Confluent, and Matthias J. Sax, Engineer, Confluent. The Google Dataflow team has done a fantastic job in evangelizing their model of handling […]
Event sourcing as an application architecture pattern is rising in popularity. Event sourcing involves modeling the state changes made by applications as an immutable sequence or “log” of events. Instead […]
A few months ago, we announced the release of open-source Confluent Platform 3.0 and Apache Kafka 0.10, marking the availability of Kafka Streams — the new stream processing engine of […]
This blog post is written jointly by Stephan Ewen, CTO of data Artisans, and Neha Narkhede, CTO of Confluent. Stephan Ewen is PMC member of Apache Flink and co-founder and CTO […]
This blog post is the third in a series about the Streams API in Kafka, the new stream processing library of the Apache Kafka project, which was introduced in Kafka […]
It is August already, and this marks exactly one year of monthly “Log Compaction” blog posts – summarizing news from the very active Apache Kafka and stream processing community. Hope […]
This blog post is the second in a series about the Streams API in Kafka, the new stream processing library of the Apache Kafka project, which was introduced in Kafka […]
This blog post is the first in a series about the Streams API in Kafka, the new stream processing library of the Apache Kafka project, which was introduced in Kafka […]
