DatriseAI-first ETL

Bloomerang Microsoft SQL Server

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

How Datrise loads Bloomerang into Microsoft SQL Server

Datrise syncs Bloomerang's contacts, accounts, deals, activities, and lifecycle events 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

Bloomerang: Nonprofit CRM for donors, campaigns, and stewardship.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Bloomerang entities map to Microsoft SQL Server

Bloomerang entityMicrosoft SQL Server objectNotes
contactsbloomerang_contactsid PK · custom fields → NVARCHAR(MAX) JSON columns
accountsbloomerang_accountsid PK · linked to bloomerang_contacts
dealsbloomerang_dealsid PK · linked to bloomerang_contacts
activitiesbloomerang_activitiesdatetime2 events

FAQ

How does Datrise handle Bloomerang'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 Bloomerang 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

Early access

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