Parquet File to Azure Synapse Integration

How Datrise loads Parquet File into Azure Synapse

Datrise syncs Parquet File's row groups, columns, schemas, partitions, file batches, and column statistics 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: Columnar Parquet files from lakes and exports.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Parquet File entities map to Azure Synapse

Parquet File entity	Azure Synapse object	Notes
row groups	`parquet_file_row_groups`	id PK · custom fields → NVARCHAR(MAX) JSON columns
columns	`parquet_file_columns`	id PK · linked to parquet_file_row_groups
schemas	`parquet_file_schemas`	id PK · linked to parquet_file_row_groups
partitions	`parquet_file_partitions`	id PK · linked to parquet_file_row_groups

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

Early access

Connect Parquet File to Azure Synapse the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.