In the second part of a series on using Redpanda for gaming, the focus is on creating real-time leaderboards, a crucial feature for enhancing competitive gameplay in the gaming industry. The discussion emphasizes the need for a robust architecture to handle the massive data influx and real-time performance required by leaderboards, especially as online gaming gains popularity. Redpanda is presented as a more efficient alternative to Apache Kafka, offering speed, simplicity, and cost-effectiveness by eliminating the need for a JVM or Apache Zookeeper. The article details a practical implementation using Redpanda for data streaming and Materialize for real-time analytics, showcasing a system that ingests player scores from various gaming frontends and processes them to deliver instantaneous leaderboard updates. This approach addresses the demands of modern gamers by ensuring low latency and accurate performance feedback, leveraging Docker, Python, and SQL to manage and query the data efficiently. The example highlights the integration of Redpanda and Materialize to achieve scalable and reliable real-time data processing, ultimately providing a seamless gaming experience for millions of concurrent users.