Fleet telemetry, cold-chain visibility, edge to cloud.
Arc is the columnar analytical database for logistics, fleet, and supply chain teams who track thousands of assets generating continuous telemetry. Unified visibility from edge to cloud. Years of history. Audit-ready in SQL.
Single Go binary. Open Parquet. Standard SQL.
The shape of the problem
A modern fleet, whether trucks, containers, ships, or last-mile vehicles, generates continuous telemetry from every asset. Location, speed, fuel, engine state, door events, temperature, humidity, shock. Multiply by thousands of assets, multiply again by 24/7 operation, and you have a high-volume time-series problem that the original fleet management system was never built to hold.
Cold-chain operations are worse. Every container, every reefer, every shipment generates temperature and humidity records every few seconds for days at a time, and regulators and customers require every reading to be retained and queryable. The data exists, but pulling a year of cold-chain history for one customer’s audit is a person-week of work.
Three places: the telematics portal for live tracking, the warehouse for analysis, a spreadsheet for the audit. Cross-system questions are slow or impossible.
Arc is the unified data layer underneath. Ingest from every asset, every gateway, every system. Hold years of history at full resolution. Query across the whole fleet in SQL.
Built for the workloads logistics actually runs
Fleet-wide telemetry at asset scale
Thousands of vehicles, containers, or shipments each emitting continuous telemetry add up to high-volume time-series data. Arc ingests at sustained rates up to 19.9M records/sec on a single instance and treats asset ID, route, customer, and shipment ID as ordinary column data, not as an exploding index.
Cold-chain compliance and audit prep
Cold-chain operations are governed by regulatory and customer requirements that demand the full temperature history of every shipment be retained and produced on request. Arc holds the entire history as compressed Parquet, queryable in SQL. Pulling a year of temperature data for one customer's audit is a query, not a project.
Route and fleet performance analysis
Comparing fuel efficiency, idle time, on-time delivery, or driver behavior across the fleet requires joining telemetry from every asset over long windows. Arc makes those queries fast and cheap to run, so the analysis becomes routine instead of quarterly.
Edge-to-cloud architecture
Vehicles and remote sites have intermittent connectivity. Arc's single-binary architecture runs at the edge on modest hardware, buffers data locally, and syncs to a central instance when connectivity returns. Same database, same SQL, same Parquet at the edge and in the cloud.
Real-time operations dashboards
Dispatch and operations teams need live visibility on what is happening right now. Arc makes data queryable about 100 milliseconds after it lands, so live tracking, alerting, and exception management run on fresh data without a separate streaming pipeline.
What Arc gives a logistics operation
One source of truth across vendors
Most logistics operations run on a patchwork of telematics vendors and platforms, each with its own portal and export format. Arc ingests from all of them and stores unified telemetry as columnar Parquet. The same SQL query covers the whole fleet, regardless of which vendor's hardware produced the data.
Years of history on object storage
Arc stores everything as ZSTD-compressed Parquet, 5-7x smaller than raw. Years of fleet and cold-chain history cost object-storage prices, not premium-database prices. Customer audits spanning multiple years become trivial.
Audit-ready cold-chain data
Cold-chain temperature and humidity records are retained at full resolution. Producing the full thermal history for a single shipment, or a year of shipments for a single customer, is a SQL query that runs in seconds.
Edge resilience
Trucks lose signal. Ships go dark. Remote sites have poor connectivity. Arc runs locally on modest hardware, buffers, and syncs when connectivity returns. The fleet keeps reporting whether the central system can hear it or not.
Standard SQL, no proprietary platform
Arc speaks standard SQL through DuckDB. Operations analysts, fleet managers, and customer-success teams who know SQL are immediately productive. The data does not live inside a closed telematics platform you have to export from.
Why logistics teams choose Arc over the alternatives
Telematics vendor platforms are excellent at live tracking and weak at long history. The export and query story usually involves CSVs and quarterly reports. Arc unifies live telemetry and historical archive in one queryable store.
Cloud data warehouses are great for BI on settled data and the wrong tool for continuous telemetry. The bill from running cross-fleet queries on a warehouse-priced engine scales badly. Arc keeps the data on storage you own.
Tag-indexed time-series databases hit a cardinality wall once you tag with asset ID, shipment ID, route, and customer. Arc handles that as column data.
Build-it-yourself DuckDB + Parquet is exactly what Arc is. DuckDB plus the streaming ingest, edge resilience, autonomous compaction, retention, and operational layer a fleet actually needs in production.
What this looks like in production
Arc is running in production logistics and asset-tracking workloads today. Continuous fleet telemetry, multi-year archives, edge-to-cloud deployments on customer-owned storage. SQL across the entire fleet and the entire history.
AGPL-3.0 with a commercial license for organizations that need it.
Get started
See it run on fleet data
Our live demos include vessel and fleet tracking workloads against real Arc instances.
Get Arc
Arc is open source and ships as a precompiled single binary. Pull it from the download page as Docker, Helm, or a .deb, and point your telematics pipeline at it. Source on GitHub.
Talk to us about your fleet
For multi-vendor or cold-chain operations looking to unify visibility and meet customer or regulatory audit requirements, we run a discovery to scope ingestion and the audit use cases that matter.