Edge Computing
Edge computing is the practice of processing data near where it is generated, on or close to the device, rather than sending all of it to a central cloud. It reduces latency, cuts bandwidth costs, and keeps working when connectivity is poor.
Why processing moves to the edge
When you have thousands of sensors or devices in the field, shipping every raw reading to a central cloud is slow and expensive. Edge computing pushes some storage and processing out to the device or a local gateway, so decisions can be made locally and only the important data travels onward.
This matters most in industrial settings, vehicles, remote sites, and anywhere bandwidth or connectivity is limited. A local store can buffer and analyze data at the edge, then sync summaries or full history to the cloud when it makes sense.
The pattern is edge for immediacy and resilience, cloud for fleet-wide analytics.
How Arc handles Edge Computing
Arc is a single Go binary with no heavy dependencies, so it can run at the edge on modest hardware and also in the cloud for fleet-wide analytics. The same database works in both places, with data stored as portable Parquet.
Arc is a high-performance columnar database. Open Parquet on storage you own, single Go binary, production-ready in 30 seconds.