Choosing Stream Processing Tools Based on Latency Needs
The fundamental lesson from years of big data work is straightforward: solve problems with tools designed for those problems. Organizations routinely force large-scale data through mismatched infrastructure — pushing streams through micro-batching systems, analyzing graphs as tables, handling real-time requirements with batch windows. Each mismatch adds latency, complexity, and operational burden. Stream processing deserves particular…
