DatriseAI-first ETL

Tempo to Birst Integration

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

How Datrise loads Tempo into Birst

Datrise syncs Tempo's worklogs, accounts, projects, users, teams, and billable hours into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.

Ideal for networked, governed enterprise BI.

Endpoints

Tempo: Time tracking and worklogs layered on Jira.

Birst: Cloud BI with networked analytics and enterprise semantic layers.

How Tempo entities map to Birst

Tempo entityBirst objectNotes
worklogstempo_worklogsid PK · custom fields → flattened 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 Birst?

Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Birst types.

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

It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.

Related pipelines

Early access

Connect Tempo to Birst 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.