In this tutorial, you are going to learn about QuestDB SQL extensions which prove to be very useful with time-series data. Using some sample data sets, you will learn how designated timestamps work and how to use extended SQL syntax to write queries on time-series data.
Introduction
Traditionally, SQL has been used for relational databases and data warehouses. However, in recent years there has been an exponential increase in the amount of data that connected systems produce, which has brought about a need for new ways to store and analyze such information. For this reason, time-series analytics have proved critical for making sense of real-time market data in financial services, sensor data from IoT devices, and application metrics.