DatriseAI-first ETL

Glassfrog Azure Synapse

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

How Datrise loads Glassfrog into Azure Synapse

Datrise syncs Glassfrog'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

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

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Glassfrog entities map to Azure Synapse

Glassfrog entityAzure Synapse objectNotes
recordsglassfrog_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventsglassfrog_eventsdatetime2 events
configuration objectsglassfrog_configuration_objectsid PK · linked to glassfrog_records

FAQ

How does Datrise handle Glassfrog'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 Glassfrog 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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