Jobber → Neon
AI-first ETL from Jobber into Neon. Governed entities, incremental sync, typed landing tables.
How Datrise loads Jobber into Neon
Datrise syncs Jobber's contacts, accounts, deals, activities, and lifecycle events into Neon as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.
Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.
Ideal for serverless Postgres workloads that scale to zero between syncs.
Endpoints
Jobber: Field service CRM for scheduling, jobs, and customer history.
Neon: Serverless Postgres destination with branching and autoscaling.
How Jobber entities map to Neon
| Jobber entity | Neon object | Notes |
|---|---|---|
| contacts | jobber_contacts | id PK · custom fields → jsonb columns |
| accounts | jobber_accounts | id PK · linked to jobber_contacts |
| deals | jobber_deals | id PK · linked to jobber_contacts |
| activities | jobber_activities | timestamptz events |
FAQ
How does Datrise handle Jobber's custom fields in Neon?
Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Neon types.
How does the Jobber to Neon sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.
Related pipelines
More destinations for Jobber
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