DatriseAI-first ETL

Zoom Microsoft SQL Server

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

How Datrise loads Zoom into Microsoft SQL Server

Datrise syncs Zoom's meetings, participants, webinars, recordings, and usage reports 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

Zoom: Video meetings, webinars, and workplace collaboration.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Zoom entities map to Microsoft SQL Server

Zoom entityMicrosoft SQL Server objectNotes
meetingszoom_meetingsid PK · custom fields → NVARCHAR(MAX) JSON columns
participantszoom_participantsid PK · linked to zoom_meetings
webinarszoom_webinarsid PK · linked to zoom_meetings
recordingszoom_recordingsid PK · linked to zoom_meetings

FAQ

How does Datrise handle Zoom'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 Zoom 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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