Today we are releasing function pipelines, a new feature that allows you to analyze data by composing multiple functions in SQL - introducing a simpler, cleaner way of expressing complex logic in PostgreSQL.
Get a primer on percentile approximations, why they're useful for analyzing large time-series data sets, and how we created the percentile approximation hyperfunctions to be efficient to compute, parallelizable, and useful with continuous aggregates and other advanced TimescaleDB features.
Get a primer on PostgreSQL aggregation, how PostgreSQL’s implementation inspired us as we built TimescaleDB hyperfunctions and its integrations with advanced TimescaleDB features – and what this means for developers.
TimescaleDB hyperfunctions are pre-built functions for the most common and difficult queries that developers write today in TimescaleDB and PostgreSQL. Hyperfunctions help developers measure what matters in time-series data, which generates massive, ever-growing streams of information.
We're excited to announce Timescale Analytics, a new project focused on combining all of the capabilities SQL needs to perform time-series analytics into one Postgres extension. Learn about our plans, why we're sharing it now, and ways to contribute your feedback and ideas.
