DatriseAI-first ETL

Google Directory to DuckDB Integration

AI-first ETL from Google Directory into DuckDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Directory into DuckDB

Datrise syncs Google Directory's users, groups, group members, organizational units, devices, and roles 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

Google Directory: Workspace user, group, and device directory.

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

How Google Directory entities map to DuckDB

Google Directory entityDuckDB objectNotes
usersgoogle_directory_usersid PK · custom fields → JSON or STRUCT columns
groupsgoogle_directory_groupsid PK · linked to google_directory_users
group membersgoogle_directory_group_membersid PK · linked to google_directory_users
organizational unitsgoogle_directory_organizational_unitsid PK · linked to google_directory_users

FAQ

How does Datrise handle Google Directory'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 Google Directory 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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