DatriseAI-first ETL

Partnerstack to Redash Integration

AI-first ETL from Partnerstack into Redash. Governed entities, incremental sync, typed landing tables.

How Datrise loads Partnerstack into Redash

Datrise syncs Partnerstack's partners, customers, transactions, rewards, links, and group memberships 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

Partnerstack: Partner, affiliate, and reseller program management.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Partnerstack entities map to Redash

Partnerstack entityRedash objectNotes
partnerspartnerstack_partnersid PK · custom fields → flattened columns for query results
customerspartnerstack_customersid PK · linked to partnerstack_partners
transactionspartnerstack_transactionsid PK · linked to partnerstack_partners
rewardspartnerstack_rewardsid PK · linked to partnerstack_partners

FAQ

How does Datrise handle Partnerstack'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 Partnerstack to Redash sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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