The rapid growth of Internet of Things (IoT) devices has led to large-scale continuous data streams that require realtime processing. Traditional cloud-centric architectures fail to meet low-latency and bandwidth efficiency requirements due to network delays and high data transmission overhead. This paper proposes EdgeStream, a lightweight edge-based framework for real-time streaming analytics in IoT environments. The system integrates edge nodes for local processing with a cloud backend for coordination and storage, using MQTT-based communication and distributed processing with anomaly detection. Analytical models for latency, throughput, and bandwidth are developed to evaluate performance. Experimental results, compared to cloudbased systems, show up to 92.8