DatriseAI-first ETL

Microsoft Teams to Microsoft SQL Server Integration

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

How Datrise loads Microsoft Teams into Microsoft SQL Server

Datrise syncs Microsoft Teams's teams, channels, messages, users, meetings, and call records 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

Microsoft Teams: Team chat, channels, and meeting activity.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Microsoft Teams entities map to Microsoft SQL Server

Microsoft Teams entityMicrosoft SQL Server objectNotes
teamsmicrosoft_teams_teamsid PK · custom fields → NVARCHAR(MAX) JSON columns
channelsmicrosoft_teams_channelsid PK · linked to microsoft_teams_teams
messagesmicrosoft_teams_messagesid PK · linked to microsoft_teams_teams
usersmicrosoft_teams_usersid PK · linked to microsoft_teams_teams

FAQ

How does Datrise handle Microsoft Teams'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 Microsoft Teams 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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