A Time-Series Database is a specialized type of database designed to handle time-stamped data efficiently. This data often comes from sources like sensors, financial markets, or web applications, where each entry is associated with a specific time. Time-series databases excel in storing, retrieving, and analyzing large volumes of data that change over time, making them ideal for monitoring trends and patterns. These databases typically offer features such as data compression, downsampling, and real-time analytics. Popular examples include InfluxDB, Prometheus, and TimescaleDB. By optimizing for time-based queries, they enable users to gain insights from their data more effectively.