Logistics & Edge Automation

Warehouses, yards, cold-chain lanes, and factory logistics all produce physical operations data: AGV poses, sorter lane metrics, RFID reads, pallet state, sensor health, and exception events. ZeptoDB keeps those timelines queryable for replay, geofencing, anomaly detection, and agent workflows.

Why logistics teams choose ZeptoDB

Entity timelines

Reconstruct pallet, RFID tag, shipment, AGV, or sorter-lane history with ordered time-series queries and ASOF JOIN.

Spatial SQL

Use haversine, ST_Distance, and ST_Within for AGV proximity checks, geofences, drone zones, and yard automation.

High-rate ingest

Ingest AGV pose streams, sorter metrics, RFID reads, and cold-chain sensors through HTTP, Arrow IPC, MessagePack, Telegraf, Kinesis, ROS 2, OPC-UA, MQTT, or Kafka paths.

Audit-grade trails

Use append-only ingest, table ACLs, S3-backed Parquet retention, and per-shipment symbols for cold-chain and regulated lane evidence.

Agent memory

Store exception notes, prior remediation, operator decisions, and model/tool calls beside the live logistics timeline.

Workloads

Workload	Typical rows/sec target	Query proof
AGV pose streams	200,000	Geofence and proximity filters
Sorter lane events	1,000,000	Per-lane jam and anomaly aggregates
RFID reads	50,000	Entity timeline reconstruction
Cold-chain sensors	100,000	Audit range scan by shipment

These are benchmark shapes, not blanket production guarantees. Use the benchmark criteria when publishing or comparing results.

The factory 10KHz live competitor proof completed at a fixed 10,000 rows/sec target for 60 seconds across ZeptoDB, InfluxDB, and TimescaleDB. All three systems inserted and verified 600,000 rows with zero failed rows in that sustained-rate proof. See Benchmarks for the exact table and scope.

Example: AGV geofence

SELECT agv_id, timestamp
FROM agv_pose
WHERE ST_Within(lat, lon, 37.7749, -122.4194, 50)

Example: pallet timeline with AGV state

SELECT p.timestamp, p.state, p.zone, a.lat, a.lon
FROM pallet_events p
ASOF JOIN agv_pose a
ON p.agv_id = a.agv_id AND p.timestamp >= a.timestamp
WHERE p.pallet_id = 10042
ORDER BY p.timestamp ASC

Example: cold-chain audit table

CREATE TABLE cold_chain_events (
  timestamp TIMESTAMP_NS,
  shipment_id SYMBOL,
  pallet_id SYMBOL,
  sensor_id SYMBOL,
  route_id SYMBOL,
  temperature_c FLOAT64,
  humidity_pct FLOAT64,
  door_open BOOL,
  quality INT32
)