DatriseAI-first ETL

Snowflake to Azure Synapse Integration

AI-first ETL from Snowflake into Azure Synapse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Snowflake into Azure Synapse

Datrise syncs Snowflake's databases, schemas, tables, views, query history, and warehouses into Azure Synapse 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 COPY into staging, then a MERGE on stable id, so re-runs update only what changed. Hash distribution on the join id with date partitioning on facts. Synapse dedicated pools reward good hash-distribution choices, so Datrise distributes on entity ids to avoid data-movement-heavy joins.

Ideal for Azure analytics estates feeding Power BI.

Endpoints

Snowflake: Cloud data platform with separated storage and compute.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Snowflake entities map to Azure Synapse

Snowflake entityAzure Synapse objectNotes
databasessnowflake_databasesid PK · custom fields → NVARCHAR(MAX) JSON columns
schemassnowflake_schemasid PK · linked to snowflake_databases
tablessnowflake_tablesid PK · linked to snowflake_databases
viewssnowflake_viewsid PK · linked to snowflake_databases

FAQ

How does Datrise handle Snowflake's custom fields in Azure Synapse?

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 Azure Synapse types.

How does the Snowflake to Azure Synapse sync stay up to date?

It runs incrementally — Datrise uses COPY into staging, then a MERGE on stable id.

Related pipelines

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