DatriseAI-first ETL

MongoDB Microsoft SQL Server

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

How Datrise loads MongoDB into Microsoft SQL Server

Datrise syncs MongoDB's collections, documents, change streams, and schema snapshots 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

MongoDB: Document database often used as an operational source for analytics.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How MongoDB entities map to Microsoft SQL Server

MongoDB entityMicrosoft SQL Server objectNotes
collectionsmongodb_collectionsid PK · custom fields → NVARCHAR(MAX) JSON columns
documentsmongodb_documentsid PK · linked to mongodb_collections
change streamsmongodb_change_streamsdatetime2 events
schema snapshotsmongodb_schema_snapshotsid PK · linked to mongodb_collections

FAQ

How does Datrise handle MongoDB'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 MongoDB 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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