Dremio to Microsoft SQL Server Integration

How Datrise loads Dremio into Microsoft SQL Server

Datrise syncs Dremio's datasets, tables, reflections, query jobs, sources, and table schemas 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

Dremio: Lakehouse query engine over open table formats.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Dremio entities map to Microsoft SQL Server

Dremio entity	Microsoft SQL Server object	Notes
datasets	`dremio_datasets`	id PK · custom fields → NVARCHAR(MAX) JSON columns
tables	`dremio_tables`	id PK · linked to dremio_datasets
reflections	`dremio_reflections`	id PK · linked to dremio_datasets
query jobs	`dremio_query_jobs`	id PK · linked to dremio_datasets

FAQ

How does Datrise handle Dremio'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 Dremio 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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