PostgreSQL is a popular choice for storing time-series data due to its familiarity among developers, although it may not be the first target for this use case. The database can handle various types of time-series data, including metrics, logs, and payment records. To scale PostgreSQL for efficient storage of large amounts of time-series data, approaches such as partitioning and indexing are often employed. Additionally, the Timescale extension provides a dedicated solution for storing time-series data in PostgreSQL, offering features like efficient data compression and aggregation. By leveraging these scalable approaches, developers can efficiently store and analyze their time-series data within the PostgreSQL framework.