DatriseAI-first ETL

Tempo to Microsoft SQL Server Integration

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

How Datrise loads Tempo into Microsoft SQL Server

Datrise syncs Tempo's worklogs, accounts, projects, users, teams, and billable hours into Microsoft SQL Server 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 a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Tempo: Time tracking and worklogs layered on Jira.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Tempo entities map to Microsoft SQL Server

Tempo entityMicrosoft SQL Server objectNotes
worklogstempo_worklogsid PK · custom fields → NVARCHAR(MAX) JSON 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 Microsoft SQL Server?

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 Microsoft SQL Server types.

How does the Tempo to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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