DatriseAI-first ETL

Teradata D Azure Synapse

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

How Datrise loads Teradata D into Azure Synapse

Datrise syncs Teradata D'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

Teradata D: SaaS or API data source for analytics and warehouse sync.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Teradata D entities map to Azure Synapse

Teradata D entityAzure Synapse objectNotes
recordsteradata_d_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventsteradata_d_eventsdatetime2 events
configuration objectsteradata_d_configuration_objectsid PK · linked to teradata_d_records

FAQ

How does Datrise handle Teradata D'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 Teradata D 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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