Clockify to Neon Integration
AI-first ETL from Clockify into Neon. Governed entities, incremental sync, typed landing tables.
How Datrise loads Clockify into Neon
Datrise syncs Clockify's time entries, projects, tasks, users, clients, and tags into Neon as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.
Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.
Ideal for serverless Postgres workloads that scale to zero between syncs.
Endpoints
Clockify: Time tracking across projects and teams.
Neon: Serverless Postgres destination with branching and autoscaling.
How Clockify entities map to Neon
| Clockify entity | Neon object | Notes |
|---|---|---|
| time entries | clockify_time_entries | id PK · custom fields → jsonb 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 Neon?
Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Neon types.
How does the Clockify to Neon sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.
Related pipelines
More destinations for Clockify
Early access
Connect Clockify to Neon 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.