
The landscape of data engineering has undergone a seismic shift, moving from the predictable but restrictive territories of all-in-one platforms to a dynamic and fragmented frontier of specialized, best-in-class tools. This fundamental change reflects a broader evolution in how organizations approach data, prioritizing agility, scalability, and developer empowerment over the perceived safety of a single, integrated solution. While older, monolithic










