Sensor Data
Sensor data is the stream of measurements produced by physical sensors monitoring the real world: temperature, vibration, pressure, humidity, location, and more. It is the raw input for IoT, industrial monitoring, and predictive maintenance.
The scale problem with sensor data
A single sensor produces a modest trickle of readings. The challenge is scale. A factory, a vehicle fleet, or a power grid can have tens or hundreds of thousands of sensors, each reading multiple times per second. The combined stream becomes millions of timestamped records per second.
That volume strains both ingestion and storage. Teams are often forced to choose: keep everything and pay a large storage bill, or aggregate and drop detail to save money. The second choice quietly throws away the resolution that future analysis might need.
Sensor data is classic time-series data, and it is best served by systems built for high-volume timestamped workloads.
How Arc handles Sensor Data
Arc ingests sensor data at fleet scale, millions of readings per second, and stores it as cheap compressed Parquet. That means industrial teams can keep full-resolution sensor history instead of aggregating it away to control cost.
Arc is a high-performance columnar database. Open Parquet on storage you own, single Go binary, production-ready in 30 seconds.