Microsoft Teams to DuckDB Integration

How Datrise loads Microsoft Teams into DuckDB

Datrise syncs Microsoft Teams's teams, channels, messages, users, meetings, and call records into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

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

DuckDB: In-process analytics database for fast local OLAP.

How Microsoft Teams entities map to DuckDB

Microsoft Teams entity	DuckDB object	Notes
teams	`microsoft_teams_teams`	id PK · custom fields → JSON or STRUCT columns
channels	`microsoft_teams_channels`	id PK · linked to microsoft_teams_teams
messages	`microsoft_teams_messages`	id PK · linked to microsoft_teams_teams
users	`microsoft_teams_users`	id PK · linked to microsoft_teams_teams

FAQ

How does Datrise handle Microsoft Teams's custom fields in DuckDB?

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

How does the Microsoft Teams to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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