Mindbody to DuckDB Integration

How Datrise loads Mindbody into DuckDB

Datrise syncs Mindbody's clients, class bookings, memberships, staff, sales, and appointments into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

Mindbody: Booking and membership platform for wellness studios.

DuckDB: In-process analytics database for fast local OLAP.

How Mindbody entities map to DuckDB

Mindbody entity	DuckDB object	Notes
clients	`mindbody_clients`	id PK · custom fields → JSON or STRUCT columns
class bookings	`mindbody_class_bookings`	id PK · linked to mindbody_clients
memberships	`mindbody_memberships`	id PK · linked to mindbody_clients
staff	`mindbody_staff`	id PK · linked to mindbody_clients

FAQ

How does Datrise handle Mindbody's custom fields in DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the Mindbody to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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