Time-series data is now everywhere and increasingly used to power core applications. It also creates a number of technical challenges: to ingest high volumes of data; to ask complex, queries for recent and historical time intervals; to perform time-centric analysis and data management. And this data doesn’t exist in isolation: entries are often joined against other relational data to ask key business questions. In this talk, I offer an overview of how we developed TimescaleDB, a new open-source database designed for time series workloads, engineered up as a plugin to PostgreSQL, in order to simplify time-series application development. Unlike most time-series newcomers, TimescaleDB supports full SQL while achieving fast ingest and complex queries. This enables developers to avoid today’s polyglot architectures and their corresponding operational and application complexity.