This article discusses time series databases, specifically InfluxDB, which is designed to efficiently store and manage large amounts of time-stamped data. Time series data has trends and captures a point in time, making it essential for various applications such as IoT, real-time analytics, and retail sales forecasting. InfluxDB offers scalability, usability, and increased productivity compared to traditional storage mechanisms. The article provides step-by-step instructions on setting up InfluxDB using R language, connecting to the database, writing data, querying data, and making predictions using time-series models. It highlights the benefits of using a time series database like InfluxDB for real-time applications and provides resources for further learning and optimization.