Tag Archives: AI and Machine Learning

Databricks vs Snowflake: A Critical Comparison of Modern Data Platforms

This article provides a critical, side-by-side comparison of Databricks and Snowflake, drawing on real-world experience leading enterprise data platform teams. It covers their origins, architecture, programming language support, workload fit, operational complexity, governance, AI capabilities, and ecosystem maturity. The guide helps architects and data leaders understand the philosophical and technical trade-offs, whether prioritising AI-native flexibility and open-source alignment with Databricks or streamlined governance and SQL-first simplicity with Snowflake. Practical recommendations, strategic considerations, and guidance by team persona equip readers to choose or combine these platforms to align with their data strategy and talent strengths.

Continue reading

MapReduce: A 20-Year Retrospective on How Jeffrey Dean and Sanjay Ghemawat Revolutionised Data Processing

This article provides a retrospective on the 20th anniversary of Jeffrey Dean and Sanjay Ghemawat’s seminal paper, “MapReduce: Simplified Data Processing on Large Clusters”. It explores the paper’s lasting impact on data processing, its influence on the development of big data technologies like Hadoop, and its broader implications for industries ranging from digital advertising to healthcare. The article also looks ahead to future trends in data processing, including stream processing and AI, emphasising how MapReduce’s principles will continue to shape the future of distributed computing.

Continue reading