DatriseAI-first ETL

Amazon S3 Azure Synapse

AI-first ETL from Amazon S3 into Azure Synapse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Amazon S3 into Azure Synapse

Datrise syncs Amazon S3'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

Amazon S3: SaaS or API data source for analytics and warehouse sync.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Amazon S3 entities map to Azure Synapse

Amazon S3 entityAzure Synapse objectNotes
recordss3_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventss3_eventsdatetime2 events
configuration objectss3_configuration_objectsid PK · linked to s3_records

FAQ

How does Datrise handle Amazon S3'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 Amazon S3 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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