Telemetry Data
Telemetry data is measurements and signals collected automatically from remote or distributed sources, then transmitted to a central system for monitoring and analysis. It covers everything from server metrics to industrial sensor readings to vehicle diagnostics.
Where telemetry data comes from
The word means "remote measurement". Anything that emits a steady stream of timestamped readings produces telemetry: a server reporting CPU and memory, a wind turbine reporting vibration and temperature, a car reporting speed and engine status, an application reporting request counts and errors.
Telemetry is high volume and continuous. A single source might emit a reading every second, and a fleet of thousands multiplies that fast. It is almost always appended rather than updated, and it is almost always queried by time range. That shape is exactly what time-series and columnar analytical databases are built for.
The challenge is rarely collecting telemetry. It is storing it affordably and querying it fast once the volume gets serious.
How Arc handles Telemetry Data
Arc is built for telemetry at scale. It ingests millions of readings per second, stores them as compressed Parquet, and lets you query across the whole fleet with SQL. You keep full-resolution telemetry without the storage bill forcing you to downsample.
Arc is a high-performance columnar database. Open Parquet on storage you own, single Go binary, production-ready in 30 seconds.