Tag: Big Data

Spark Isn’t Magic: What Twenty Years of Data Engineering Taught Me About Distributed Processing

Posted on 6 min read

Every few years, a technology emerges that fundamentally changes how we think about data processing. MapReduce did it in 2004. Apache Spark did it in 2014. And after spending two decades building data pipelines across enterprises of every size, I’ve learned that the difference between a successful Spark implementation and a failed one rarely comes… Continue reading

Why Kafka Became the Backbone of Modern Data Architecture: Lessons from Building Event-Driven Systems at Scale

Posted on 6 min read

When LinkedIn open-sourced Kafka in 2011, few predicted it would become the de facto standard for real-time data streaming. Fourteen years later, Kafka processes trillions of messages daily across organizations of every size, from startups to Fortune 500 companies. Having architected event-driven systems for over two decades, I’ve watched Kafka evolve from an interesting alternative… Continue reading

Data Lakehouse Architecture: Bridging Data Lakes and Data Warehouses

Posted on 5 min read

After two decades of building data platforms, I’ve witnessed the pendulum swing between data lakes and data warehouses multiple times. Organizations would invest heavily in one approach, hit its limitations, then pivot to the other. The data lakehouse architecture represents something different—a genuine synthesis that addresses the fundamental trade-offs that forced us to choose between… Continue reading