Real-Time Analytics Is Often Overkill — Here Is What Most Teams Actually Need

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A DEV Community article argues that most data teams conflate 'real-time analytics' with genuinely different requirements, ranging from sub-second event streaming to overnight batch refreshes. True real-time infrastructure — using tools like Kafka or Flink — is only justified for use cases such as fraud detection, live trading, or active system monitoring. For the majority of business analytics needs, pre-aggregated caching that refreshes every 15 minutes delivers query results in milliseconds while keeping data only minutes old. This approach achieves fast response times, reasonable data freshness, and consistent metrics at a fraction of the cost and complexity of a full streaming architecture. The article concludes that roughly 90% of what teams label 'real-time' is adequately served by frequent-refresh caching rather than event-driven pipelines.

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