DatriseAI-first ETL

Gainsight to Redash Integration

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

How Datrise loads Gainsight into Redash

Datrise syncs Gainsight's customers, health scores, playbooks, tasks, surveys, and usage metrics 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

Gainsight: Customer success health scoring and playbooks.

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

How Gainsight entities map to Redash

Gainsight entityRedash objectNotes
customersgainsight_customersid PK · custom fields → flattened columns for query results
health scoresgainsight_health_scoresid PK · linked to gainsight_customers
playbooksgainsight_playbooksid PK · linked to gainsight_customers
tasksgainsight_tasksid PK · linked to gainsight_customers

FAQ

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

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

Related pipelines

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