Clockify to Azure Synapse Integration

How Datrise loads Clockify into Azure Synapse

Datrise syncs Clockify's time entries, projects, tasks, users, clients, and tags 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

Clockify: Time tracking across projects and teams.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Clockify entities map to Azure Synapse

Clockify entity	Azure Synapse object	Notes
time entries	`clockify_time_entries`	id PK · custom fields → NVARCHAR(MAX) JSON columns
projects	`clockify_projects`	id PK · linked to clockify_time_entries
tasks	`clockify_tasks`	id PK · linked to clockify_time_entries
users	`clockify_users`	id PK · linked to clockify_time_entries

FAQ

How does Datrise handle Clockify'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 Clockify 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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