Particle to Mode Integration
AI-first ETL from Particle into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads Particle into Mode
Datrise syncs Particle's devices, events, variables, firmware versions, product fleets, and device logs into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
Particle: IoT device fleet telemetry and events.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How Particle entities map to Mode
| Particle entity | Mode object | Notes |
|---|---|---|
| devices | particle_devices | id PK · custom fields → flattened columns for SQL and notebooks |
| events | particle_events | temporal 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 Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the Particle to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for Particle
Early access
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