Streaming data, characterized by its continuous flow from multiple sources, is effectively managed using time series databases, which are optimized for such data types. TimescaleDB, an extension of PostgreSQL, is celebrated for its efficient time-series query performance, supporting multi-node deployment and data chunking for better performance. The integration of Redpanda and TimescaleDB through Kafka Connect exemplifies how to build a system for analyzing real-time data streams, such as payment systems, to detect anomalies like fraud. The tutorial outlines a step-by-step process for setting up Redpanda, TimescaleDB, and Kafka Connect using Docker, showcasing a practical application for streaming time series data into a PostgreSQL-based environment for real-time analysis. This setup facilitates the creation of real-time applications across various domains, leveraging the compatibility of Redpanda with Apache Kafka API and the PostgreSQL nature of TimescaleDB to provide diverse connection options.