Apache Kafka, Apache Flink, and Apache Iceberg are among the most popular technologies in the data ecosystem. While Kafka enables you to move data around in real time, Flink allows you to process ...

In my journey through data engineering, one of the most remarkable ... real-time data architecture using technologies like Apache Kafka and cloud-native solutions, we were able to process and ...

Subscribe for free. Kafka allows the use of heterogeneous data sources and sinks – a key feature for IoT applications that can leverage Kafka to combine heterogeneous sources into a single system.

Kafka users especially appreciate how they can set up various streams of data, what are known as “Kafka topics ... Kreps seems to get off on tackling these sorts of distributed systems engineering ...

As a data engineering leader with over 15 years of ... This speed depends on streaming tools like Apache Kafka, paired with Apache Flink for fast processing—the backbone of modern real-time ...

streaming data become common. Hatched at LinkedIn, Kafka’s founding engineering team spun out to form Confluent, which has been a primary developer of the Apache project ever since. But not the ...

Distinguished software engineering expert Purshotam Singh ... In his recent papers like "Latency Reduction Techniques in Kafka for Real-Time Data Processing Applications" in the International ...

Native Kafka integration DataForge Cloud’s new ... By bringing functional programming to data engineering, DataForge introduces a new paradigm for building data solutions. Avoid the pitfalls ...

Anderson writes in full as follows… Data engineering is the next big thing, right? With all of the hype surrounding AI and data, our industry should have this squared away, but we don’t.