In today’s fast-paced financial markets, real-time data analysis is crucial for traders, analysts, and investors to make informed decisions. Traditional batch processing techniques often fail to meet the low-latency requirements of stock market applications. This paper presents a real-time stock market data visualization system using Apache Kafka, Google Sheets, and Grafana to enable dynamic tracking of stock prices and trends. The system efficiently streams stock market data using Kafka producers, stores real-time updates in Google Sheets via Kafka consumers, and visualizes insights using Grafana dashboards. Unlike traditional database solutions, Google Sheets provides a lightweight, cost-effective, and easily accessible method for real-time data storage. The proposed solution allows users to select stocks dynamically within Grafana and analyze trends with interactive visualizations. Our implementation demonstrates the feasibility of low-cost, real-time stock market analytics without reliance on paid cloud services, making it an ideal solution for individuals and small-scale investors.