Mindbody to Redash Integration
AI-first ETL from Mindbody into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads Mindbody into Redash
Datrise syncs Mindbody's clients, class bookings, memberships, staff, sales, and appointments into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.
Ideal for lightweight, query-driven dashboards.
Endpoints
Mindbody: Booking and membership platform for wellness studios.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How Mindbody entities map to Redash
| Mindbody entity | Redash object | Notes |
|---|---|---|
| clients | mindbody_clients | id PK · custom fields → flattened columns for query results |
| 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 Redash?
Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.
How does the Mindbody to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
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