Vitally to Microsoft SQL Server Integration

How Datrise loads Vitally into Microsoft SQL Server

Datrise syncs Vitally's accounts, users, health scores, tasks, playbooks, and product usage into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Vitally: Customer success health and account analytics.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Vitally entities map to Microsoft SQL Server

Vitally entity	Microsoft SQL Server object	Notes
accounts	`vitally_accounts`	id PK · custom fields → NVARCHAR(MAX) 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 Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the Vitally to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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