DatriseAI-first ETL

Parquet File Azure Synapse

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

How Datrise loads Parquet File into Azure Synapse

Datrise syncs Parquet File's records, events, and configuration objects 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

Parquet File: SaaS or API data source for analytics and warehouse sync.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Parquet File entities map to Azure Synapse

Parquet File entityAzure Synapse objectNotes
recordsparquet_file_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventsparquet_file_eventsdatetime2 events
configuration objectsparquet_file_configuration_objectsid PK · linked to parquet_file_records

FAQ

How does Datrise handle Parquet File'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 Parquet File 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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