Particle to Domo Integration
AI-first ETL from Particle into Domo. Governed entities, incremental sync, typed landing tables.
How Datrise loads Particle into Domo
Datrise syncs Particle's devices, events, variables, firmware versions, product fleets, and device logs into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.
Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.
Ideal for all-in-one cloud BI with built-in ETL.
Endpoints
Particle: IoT device fleet telemetry and events.
Domo: Cloud BI platform combining data integration and executive dashboards.
How Particle entities map to Domo
| Particle entity | Domo object | Notes |
|---|---|---|
| devices | particle_devices | id PK · custom fields → flattened columns for Magic ETL |
| events | particle_events | date/time columns events |
| variables | particle_variables | id PK · linked to particle_devices |
| firmware versions | particle_firmware_versions | id PK · linked to particle_devices |
FAQ
How does Datrise handle Particle's custom fields in Domo?
Flexible values are stored as flattened columns for Magic ETL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Domo types.
How does the Particle to Domo sync stay up to date?
It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.
Related pipelines
More destinations for Particle
Early access
Connect Particle to Domo the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.