Distributed systems and data-intensive applications

Real-time processing of F1 event streams

Exploring F1 race data with Airflow 3, dbt and Clickhouse

We examine how RocksDB, Apache Fluss, and distributed caching layers address scaling challenges, providing both architectural guidance and practical configuration examples for production deployments.

In this series of blog posts, I explore the multi-faceted challenge of building data quality into an organization’s data ecosystem.

In this post, we'll explore different approaches for ingesting Kafka data into Iceberg tables, examine strategies for managing schema evolution, and discuss when to choose one method over another based on your specific use case.