DatriseAI-first ETL

Teradata to Azure Synapse Integration

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

How Datrise loads Teradata into Azure Synapse

Datrise syncs Teradata's tables, rows, schemas, indexes, primary indexes, and query history 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: Teradata analytical database for enterprise workloads.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Teradata entities map to Azure Synapse

Teradata entityAzure Synapse objectNotes
tablesteradata_d_tablesid PK · custom fields → NVARCHAR(MAX) JSON columns
rowsteradata_d_rowsid PK · linked to teradata_d_tables
schemasteradata_d_schemasid PK · linked to teradata_d_tables
indexesteradata_d_indexesid PK · linked to teradata_d_tables

FAQ

How does Datrise handle Teradata'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 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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