DatriseAI-first ETL

Harness to Azure Synapse Integration

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

How Datrise loads Harness into Azure Synapse

Datrise syncs Harness's pipelines, deployments, services, environments, execution logs, and approvals 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

Harness: Continuous delivery pipelines and deployment verification.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Harness entities map to Azure Synapse

Harness entityAzure Synapse objectNotes
pipelinesharness_pipelinesid PK · custom fields → NVARCHAR(MAX) JSON columns
deploymentsharness_deploymentsid PK · linked to harness_pipelines
servicesharness_servicesid PK · linked to harness_pipelines
environmentsharness_environmentsid PK · linked to harness_pipelines

FAQ

How does Datrise handle Harness'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 Harness 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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