DatriseAI-first ETL

Tempo to Neon Integration

AI-first ETL from Tempo into Neon. Governed entities, incremental sync, typed landing tables.

How Datrise loads Tempo into Neon

Datrise syncs Tempo's worklogs, accounts, projects, users, teams, and billable hours 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

Tempo: Time tracking and worklogs layered on Jira.

Neon: Serverless Postgres destination with branching and autoscaling.

How Tempo entities map to Neon

Tempo entityNeon objectNotes
worklogstempo_worklogsid PK · custom fields → jsonb columns
accountstempo_accountsid PK · linked to tempo_worklogs
projectstempo_projectsid PK · linked to tempo_worklogs
userstempo_usersid PK · linked to tempo_worklogs

FAQ

How does Datrise handle Tempo'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 Tempo 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

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