Freshdesk → Azure Synapse
AI-first ETL from Freshdesk into Azure Synapse. Governed entities, incremental sync, typed landing tables.
How Datrise loads Freshdesk into Azure Synapse
Datrise syncs Freshdesk's tickets, contacts, agents, SLA events, and satisfaction scores 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
Freshdesk: Customer support helpdesk with tickets, SLAs, and agent workflows.
Azure Synapse: Microsoft analytics workspace with SQL pools.
How Freshdesk entities map to Azure Synapse
| Freshdesk entity | Azure Synapse object | Notes |
|---|---|---|
| tickets | freshdesk_tickets | id PK · custom fields → NVARCHAR(MAX) JSON columns |
| contacts | freshdesk_contacts | id PK · linked to freshdesk_tickets |
| agents | freshdesk_agents | id PK · linked to freshdesk_tickets |
| SLA events | freshdesk_sla_events | datetime2 events |
FAQ
How does Datrise handle Freshdesk'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 Freshdesk to Azure Synapse sync stay up to date?
It runs incrementally — Datrise uses COPY into staging, then a MERGE on stable id.
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