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Robotics & drones

High-rate sensor and pose streams, fleet current-state, and geospatial queries on one engine — line-rate ingest with constant-time reads.

The problem

Why this is hard today

A robot or drone fleet emits high-rate sensor and pose telemetry continuously, and operations needs the live position and health of every unit right now — plus geospatial questions like which units have left their assigned area.

The usual stack splits pose streams into a processor, current position into a cache, and geospatial history into a warehouse — three systems that drift, and a fleet view that lags the units it tracks.

The fit is one engine that ingests pose and sensor streams at line rate, keeps per-unit current state as O(1) reads, and answers geospatial queries with built-in functions in the same SQL.

Where NYXDB fits

Use-case journeys

Pose & sensor ingest

Absorb high-rate pose and sensor streams durably, with backpressure instead of data loss.

IoT & telemetry

Live fleet dashboards

Dashboards read keyed current-state tables and subscribe to live position updates.

Real-time dashboards

Geospatial in SQL

Proximity and geofence queries with built-in geo functions over live fleet state.

IoT & telemetry

Architecture

How NYXDB fits a robot fleet

Pose and sensor events append durably at line rate under the memory governor; keyed tables hold the latest state per unit; built-in geospatial functions answer proximity and geofence questions over the same data.

  1. 01

    Line-rate ingest

    Shard-owned, lock-free write paths, WAL-backed, governed under pressure.

  2. 02

    Fleet state

    Keyed tables keep the latest pose and health per unit — O(1) reads.

  3. 03

    Geospatial

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

  4. 04

    Live streams

    STREAM SELECT pushes pose and health deltas to fleet dashboards as they commit.

Real SQL

Representative queries

Units currently out of range
SELECT unit_id, lat, lon
FROM fleet_state
WHERE distance_m > max_range_m;

Every statement follows the engine’s own test SQL shapes. See the SQL reference for full syntax.

Capabilities

What you get

Line-rate ingest

Lock-free shard-owned write paths.

Geospatial in SQL

geo_distance, geohash, and H3 cell functions.

O(1) fleet state

Latest pose and health per unit, instantly.

Edge to cloud

One 154MB image runs on-vehicle or in the datacenter.

Proof

Measured on the vetted benchmark lane

Measured on AMD EPYC 9554P 64-Core Processor (64t), 1505GB RAM, 6x NVMe — measured on server-class hardware. Release build, median of 5 (re-captured stragglers: median of 3), commit-pinned (7945ae33, 2026-07-09). Ingest figures are engine-side. See the full benchmark suite.

One engine for the fleet

Explore IoT & telemetry or run a node.