Workflow Divergence: Comparing Batch and Continuous System Architectures
Every system architect eventually faces a fork in the road: should this workflow process data in discrete chunks or as a steady stream? The choice between batch and continuous architectures is not a matter of fashion—it shapes latency, cost, fault tolerance, and the very mental model your team uses to reason about the system. This guide maps the divergence, not as a checklist of features, but as a framework for matching workflow topology to operational reality. We write for engineers who have seen both patterns in production and suspect their current choice might be suboptimal. You will leave with a structured way to evaluate the trade-offs, plus a few surprises about where each model silently fails. Why This Fork Matters Now Modern data pipelines and event-driven systems have blurred the line between batch and continuous.