DatriseAI-first ETL

Mindbody to Microsoft SQL Server Integration

AI-first ETL from Mindbody into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.

How Datrise loads Mindbody into Microsoft SQL Server

Datrise syncs Mindbody's clients, class bookings, memberships, staff, sales, and appointments 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

Mindbody: Booking and membership platform for wellness studios.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Mindbody entities map to Microsoft SQL Server

Mindbody entityMicrosoft SQL Server objectNotes
clientsmindbody_clientsid PK · custom fields → NVARCHAR(MAX) JSON columns
class bookingsmindbody_class_bookingsid PK · linked to mindbody_clients
membershipsmindbody_membershipsid PK · linked to mindbody_clients
staffmindbody_staffid PK · linked to mindbody_clients

FAQ

How does Datrise handle Mindbody'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 Mindbody 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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