DatriseAI-first ETL

Tempo to Airtable Integration

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

How Datrise loads Tempo into Airtable

Datrise syncs Tempo's worklogs, accounts, projects, users, teams, and billable hours into Airtable as a table per source entity in your base. Flexible or custom fields land in long-text JSON or linked records for nested data, and timestamps such as created, updated, and status changes are typed as date/dateTime fields.

Sync is incremental: Datrise uses upserts records matched on a stable id field, so re-runs update only what changed. Airtable enforces per-base record and API rate limits, so Datrise batches writes and lands a focused field set.

Ideal for operational workflows and light CRM views in Airtable.

Endpoints

Tempo: Time tracking and worklogs layered on Jira.

Airtable: Relational spreadsheet destination for ops and go-to-market teams.

How Tempo entities map to Airtable

Tempo entityAirtable objectNotes
worklogstempo_worklogsid PK · custom fields → long-text JSON or linked records for nested data
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 Airtable?

Flexible values are stored as long-text JSON or linked records for nested data, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Airtable types.

How does the Tempo to Airtable sync stay up to date?

It runs incrementally — Datrise uses upserts records matched on a stable id field.

Related pipelines

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