Today, TimescaleDB is launching hyperfunctions, a series of SQL functions that make it easier to manipulate and analyze time-series data with fewer lines of code. These functions, built on top of PostgreSQL, allow developers to calculate percentile approximations, compute time-weighted averages, downsample and smooth data, and perform faster COUNT DISTINCT queries using approximations. The hyperfunctions are designed to be easy to use, with the same SQL syntax as existing TimescaleDB features. They are written in Rust and can be used on hypertables or regular PostgreSQL tables. By building new SQL functions instead of introducing new syntax, TimescaleDB aims to preserve the flexibility and compatibility of its existing features while providing a more efficient and productive way to work with time-series data. The hyperfunctions are designed to simplify complex analysis and manipulation operations, bringing them closer to the data, reducing network transmission costs, and enabling faster query performance. They can be used in various use cases, such as IoT devices, IT systems, marketing analytics, user behavior, financial metrics, and more. The TimescaleDB team invites developers to try hyperfunctions with a free 30-day trial of their fully managed service or by downloading the timescaledb_toolkit extension for free.