Always Be Launching
Function Pipelines: Building Functional Programming Into PostgreSQL Using Custom Operators
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.
PostgreSQL
How Percentile Approximation Works (and Why It’s More Useful Than Averages)
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.
Product & Engineering
How PostgreSQL Aggregation Works and How It Inspired Our Hyperfunctions’ Design
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.
Always Be Launching
Introducing Hyperfunctions: New SQL Functions to Simplify Working With Time-Series Data in PostgreSQL
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.
Announcements & Releases
Time-Series Analytics for PostgreSQL: Introducing the Timescale Analytics Project
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.
