Day.ai → MySQL
AI-first ETL from Day.ai into MySQL. Governed entities, incremental sync, typed landing tables.
How Datrise loads Day.ai into MySQL
Datrise syncs Day.ai'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
Day.ai: AI-native CRM for relationship data, enrichment, and workflow automation.
MySQL: Widely used OSS relational engine (InnoDB).
How Day.ai entities map to MySQL
| Day.ai entity | MySQL object | Notes |
|---|---|---|
| contacts | day_ai_contacts | id PK · custom fields → JSON columns |
| accounts | day_ai_accounts | id PK · linked to day_ai_contacts |
| deals | day_ai_deals | id PK · linked to day_ai_contacts |
| activities | day_ai_activities | DATETIME/TIMESTAMP events |
FAQ
How does Datrise handle Day.ai'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 Day.ai 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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