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Industrial IoT

Durable, ordered device history with instant current-state reads — one engine at the edge or in the datacenter.

The problem

Why this is hard today

Industrial telemetry is unforgiving: sensor and control streams are high-volume and bursty, ordering matters, and a dropped reading can mean a missed fault.

Cloud-only pipelines add latency and a failure mode when connectivity drops; warehouse-only pipelines answer current-state questions with full-history scans.

The fit is an engine that ingests at line rate with backpressure, keeps ordered history durably, and answers "what is this machine doing now" in constant time — on hardware that runs at the edge.

Where NYXDB fits

Use-case journeys

Device telemetry at line rate

Absorb bursty device streams durably with backpressure, and read current state per device instantly.

IoT & telemetry

Fleet & process observability

Continuous transforms turn raw telemetry into live plant/line metric tables.

Observability & logs

Anomaly & threshold alerting

Read-your-writes state and exact counts drive real-time threshold checks.

Fraud & risk

Architecture

How NYXDB fits industrial IoT

Readings append at line rate under the memory governor; keyed tables keep the last reading per device for O(1) current-state reads, on a 154MB image that runs anywhere.

  1. 01

    Line-rate ingest

    Shard-owned, lock-free write paths, WAL-backed.

  2. 02

    Governed

    Ramp then block admission under memory pressure.

  3. 03

    Current state

    Keyed tables keep the latest per (device, metric).

  4. 04

    Edge deploy

    One small image from an edge box to the cloud.

Real SQL

Representative query

Machines currently over threshold
SELECT device_id, value
FROM readings
WHERE metric = 'vibration_rms' AND value > 4.5;

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.

Backpressure

Governor ramps then blocks — no data loss.

O(1) current state

Last reading per device instantly.

Edge to cloud

One 154MB image runs anywhere.

Proof

Measured on the vetted benchmark lane

2.66M rows/s

durable ingest, single core

1M-row batches (~232B, 16-col)

group-fsync default

View benchmark12.45M rows/s

in-memory columnar append ceiling

narrow 4-column rows

vetted table

View benchmark
154MB

container image, edge-ready

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.

Learn more

Related documentation

Memory governor

Ramp/block admission.

Storage model

Delta, parts, spill.

Keyed tables

Current state per device.

Telemetry that keeps up, at the edge

Explore the IoT solution or run a node.

Get started Read the docs