Window Function
A window function is a SQL feature that performs a calculation across a set of rows related to the current row, called a window, without collapsing those rows into one. It powers running totals, moving averages, rankings, and period-over-period comparisons.
What makes window functions powerful
A normal aggregate like SUM collapses many rows into one result. A window function computes across a related set of rows but keeps every row in the output. That is what lets you compute a moving average alongside each data point, or a running total that grows row by row, or each row's rank within a group.
For time-series analysis this is essential. Moving averages, rate-of-change, and comparisons to a prior period are all window-function work. They turn raw sequences into the smoothed, comparative views that analysis actually needs.
They are part of standard SQL, so any engine with good SQL support gives you them.
How Arc handles Window Function
Arc supports standard SQL window functions, so time-series work like moving averages, running totals, and period comparisons is expressed in plain SQL your team already knows, with no special query language to learn.
Arc is a high-performance columnar database. Open Parquet on storage you own, single Go binary, production-ready in 30 seconds.