DatriseAI-first ETL

Gainsight to Microsoft SQL Server Integration

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

How Datrise loads Gainsight into Microsoft SQL Server

Datrise syncs Gainsight's customers, health scores, playbooks, tasks, surveys, and usage metrics into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Gainsight: Customer success health scoring and playbooks.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Gainsight entities map to Microsoft SQL Server

Gainsight entityMicrosoft SQL Server objectNotes
customersgainsight_customersid PK · custom fields → NVARCHAR(MAX) JSON columns
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 Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the Gainsight to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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