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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 & telemetry

Live location & geospatial queries

Current position per vehicle with distance, geohash, and H3 cell functions.

Caching & real-time serving

ETA & route analytics

Continuous transforms turn telemetry into live route and ETA metrics.

Real-time dashboards

Architecture

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.

  1. 01

    Ingest telemetry

    GPS/telemetry append at line rate, WAL-backed, with backpressure not loss.

  2. 02

    Current location

    A keyed table holds the latest position per vehicle for O(1) reads.

  3. 03

    Geospatial query

    geo_distance, great_circle_distance, geohash, and H3 cell functions run in SQL.

  4. 04

    Dispatch

    Streaming reads push position and ETA updates live.

Real SQL

Representative query

Nearest vehicles by distance
SELECT vehicle_id,
geo_distance(lat, lon, 40.7580, -73.9855) AS meters
FROM vehicle_location
WHERE geo_distance(lat, lon, 40.7580, -73.9855) < 2000
ORDER BY meters
LIMIT 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

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.

One engine for the dispatch path

Explore IoT & telemetry or run a node.