As more industries require real-time data processing, selecting the optimal computing architecture has become essential. This paper explores how edge analytic tasks compare to cloud computing regarding value and speed. While cloud computing provides significant scalability and a centralized resource pool, it can struggle with applications that require quick responses. Conversely, edge computing maintains processing close to data collectors, reducing latency, though this introduces challenges in scaling and system maintenance. The article presents key performance statistics for latency, bandwidth, processing power, and security, illustrating when and where each approach is most effective. The goal is to assist leaders, IT staff, and developers in identifying the best architecture for their real-time analytics tasks.