InfluxDB is a leading platform for building time series applications, with significant advancements in machine learning algorithms like long short-term memory (LSTM) and Prophet, which have led to improved forecast accuracy. The Facebook Kats library is used for analyzing time series data, offering functionalities such as forecasting, detection, auto feature engineering, and utilities. In this article, the author learns how to use InfluxDB to store and access time series data with Python API and analyze it using Facebook Kats. Three popular time series algorithms, SARIMA, Holt-Winters, and Prophet, are introduced along with their performance comparison, showcasing the strengths of each model in capturing seasonality, autocorrelation, and increasing trend. The author concludes that InfluxDB is a powerful platform for building and operating time series applications, empowering developers to build transformative monitoring, analytics, and IoT applications faster and to scale.