Logistics & mobility
Fleet telemetry at line rate, live location state, and geospatial queries in SQL — distance, geohash, and H3 cells built in.
The problem
Why this is hard today
Logistics and mobility platforms track fleets in motion: a firehose of GPS and telemetry, current-location state that must be instant to read, and geospatial questions — nearest driver, distance to destination, which cell a vehicle is in — asked constantly. The usual stack is a telemetry pipeline, a cache for live positions, and a separate geospatial service.
The split adds latency to exactly the queries that need to be fast — "who is the nearest available vehicle" — and a freshness gap between the position that was reported and the position the dispatcher sees.
What logistics needs is line-rate telemetry ingest, current-location state as O(1) reads, and geospatial functions in the same SQL — so distance and cell queries run against the position that just arrived.
Where NYXDB fits
Use-case journeys
Fleet telemetry at line rate
Absorb GPS and telemetry durably, with backpressure instead of loss.
IoT & telemetryLive location & geospatial queries
Current position per vehicle with distance, geohash, and H3 cell functions.
Caching & real-time servingETA & route analytics
Continuous transforms turn telemetry into live route and ETA metrics.
Real-time dashboardsArchitecture
How NYXDB fits logistics & mobility
Telemetry appends at line rate under the memory governor; keyed tables hold current location per vehicle; the native geospatial family answers distance and cell queries in SQL — one engine on the dispatch path.
- 01
Ingest telemetry
GPS/telemetry append at line rate, WAL-backed, with backpressure not loss.
- 02
Current location
A keyed table holds the latest position per vehicle for O(1) reads.
- 03
Geospatial query
geo_distance, great_circle_distance, geohash, and H3 cell functions run in SQL.
- 04
Dispatch
Streaming reads push position and ETA updates live.
Real SQL
Representative query
SELECT vehicle_id, geo_distance(lat, lon, 40.7580, -73.9855) AS metersFROM vehicle_locationWHERE geo_distance(lat, lon, 40.7580, -73.9855) < 2000ORDER BY metersLIMIT 10;Every statement follows the engine’s own test SQL shapes. See the SQL reference for full syntax.
Capabilities
What you get
Line-rate telemetry
Shard-owned write paths absorb fleet streams.
Geospatial in SQL
geo_distance, great_circle_distance, geohash, and H3 cell functions.
Live location state
Keyed current position per vehicle, O(1).
Edge to cloud
One 154MB image runs at the edge or in the datacenter.
Proof
Measured on the vetted benchmark lane
durable telemetry ingest, single core
1M-row batches (~232B, 16-col)
group-fsync default
View benchmark71.6nscurrent-location point consult
warm postings
vetted table
View benchmarkcontainer image, edge-ready
geospatial functions built in
image
Measured on Apple M4 Max (dev), macOS — server-class validation pending. Release build, median of 5, commit-pinned (d4a3885b, 2026-07-07). Ingest figures are engine-side. See the full benchmark suite.
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