DatriseAI-first ETL

Google Cloud Storage F Azure Synapse

AI-first ETL from Google Cloud Storage F into Azure Synapse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Cloud Storage F into Azure Synapse

Datrise syncs Google Cloud Storage F'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

Google Cloud Storage F: SaaS or API data source for analytics and warehouse sync.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Google Cloud Storage F entities map to Azure Synapse

Google Cloud Storage F entityAzure Synapse objectNotes
recordsgoogle_cloud_storage_f_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventsgoogle_cloud_storage_f_eventsdatetime2 events
configuration objectsgoogle_cloud_storage_f_configuration_objectsid PK · linked to google_cloud_storage_f_records

FAQ

How does Datrise handle Google Cloud Storage F'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 Google Cloud Storage F 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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