Jobber → MySQL
AI-first ETL from Jobber into MySQL. Governed entities, incremental sync, typed landing tables.
How Datrise loads Jobber into MySQL
Datrise syncs Jobber's contacts, accounts, deals, activities, and lifecycle events into MySQL as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME/TIMESTAMP.
Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Optional RANGE partitioning by load date. MySQL collation matters for CRM text, so Datrise lands utf8mb4 to preserve emoji and non-Latin characters.
Ideal for operational reporting and app databases already standardized on MySQL.
Endpoints
Jobber: Field service CRM for scheduling, jobs, and customer history.
MySQL: Widely used OSS relational engine (InnoDB).
How Jobber entities map to MySQL
| Jobber entity | MySQL object | Notes |
|---|---|---|
| contacts | jobber_contacts | id PK · custom fields → JSON columns |
| accounts | jobber_accounts | id PK · linked to jobber_contacts |
| deals | jobber_deals | id PK · linked to jobber_contacts |
| activities | jobber_activities | DATETIME/TIMESTAMP events |
FAQ
How does Datrise handle Jobber's custom fields in MySQL?
Flexible values are stored as JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native MySQL types.
How does the Jobber to MySQL sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.
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