Time-Series Data
Time-series data is any sequence of data points where each point is tied to a timestamp and the order in time matters. Server metrics, sensor readings, stock prices, and application events are all time-series data.
What makes data time-series
What sets time-series data apart is that time is the primary axis. You rarely ask "show me this one record". You ask "show me how this changed over the last hour, day, or year". Trends, rates of change, and patterns over time are the whole point.
It also tends to arrive in order, in high volume, and to be written once rather than updated. Those properties let specialized systems store and query it far more efficiently than a general-purpose database.
Time-series data is everywhere now: observability, IoT, finance, energy, logistics. Any time something is measured repeatedly, you get a time series.
How Arc handles Time-Series Data
Arc is a columnar analytical database built for time-series data. It ingests it fast, stores it compressed and time-partitioned, and queries it with standard SQL including time helpers like time_bucket and date_trunc.
Arc is a high-performance columnar database. Open Parquet on storage you own, single Go binary, production-ready in 30 seconds.