DatriseAI-first ETL

Everhour to Azure Synapse Integration

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 time entries, projects, tasks, users, clients, and budgets 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: Time tracking and budgets for project teams.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Everhour entities map to Azure Synapse

Everhour entityAzure Synapse objectNotes
time entrieseverhour_time_entriesid PK · custom fields → NVARCHAR(MAX) JSON columns
projectseverhour_projectsid PK · linked to everhour_time_entries
taskseverhour_tasksid PK · linked to everhour_time_entries
userseverhour_usersid PK · linked to everhour_time_entries

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

Early access

Connect Everhour to Azure Synapse the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.