Vitally to MySQL Integration

How Datrise loads Vitally into MySQL

Datrise syncs Vitally's accounts, users, health scores, tasks, playbooks, and product usage 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

Vitally: Customer success health and account analytics.

MySQL: Widely used OSS relational engine (InnoDB).

How Vitally entities map to MySQL

Vitally entity	MySQL object	Notes
accounts	`vitally_accounts`	id PK · custom fields → JSON columns
users	`vitally_users`	id PK · linked to vitally_accounts
health scores	`vitally_health_scores`	id PK · linked to vitally_accounts
tasks	`vitally_tasks`	id PK · linked to vitally_accounts

FAQ

How does Datrise handle Vitally'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 Vitally to MySQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.

Related pipelines

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