Square → Redash
AI-first ETL from Square into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads Square into Redash
Datrise syncs Square's payments, orders, customers, catalog items, and locations 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
Square: Payments and commerce platform for retail and online sellers.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How Square entities map to Redash
| Square entity | Redash object | Notes |
|---|---|---|
| payments | square_payments | id PK · custom fields → flattened columns for query results |
| orders | square_orders | id PK · linked to square_payments |
| customers | square_customers | id PK · linked to square_payments |
| catalog items | square_catalog_items | id PK · linked to square_payments |
FAQ
How does Datrise handle Square'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 Square to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Square
Early access
Connect Square to Redash the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.