DatriseAI-first ETL

Everhour Azure Synapse

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

How Datrise loads Everhour into Azure Synapse

Datrise syncs Everhour'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

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

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Everhour entities map to Azure Synapse

Everhour entityAzure Synapse objectNotes
recordseverhour_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventseverhour_eventsdatetime2 events
configuration objectseverhour_configuration_objectsid PK · linked to everhour_records

FAQ

How does Datrise handle Everhour'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 Everhour 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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