DatriseAI-first ETL

Nimble Microsoft SQL Server

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

How Datrise loads Nimble into Microsoft SQL Server

Datrise syncs Nimble's relationship records, deals, tasks, and activity intelligence 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

Nimble: Relationship-focused CRM for SMB sales teams.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Nimble entities map to Microsoft SQL Server

Nimble entityMicrosoft SQL Server objectNotes
relationship recordsnimble_relationship_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
dealsnimble_dealsid PK · linked to nimble_relationship_records
tasksnimble_tasksid PK · linked to nimble_relationship_records
activity intelligencenimble_activity_intelligencedatetime2 events

FAQ

How does Datrise handle Nimble'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 Nimble 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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