Orbit to DuckDB Integration
AI-first ETL from Orbit into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Orbit into DuckDB
Datrise syncs Orbit's members, activities, organizations, love scores, tags, and activity types 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
Orbit: Community member activity and engagement scoring.
DuckDB: In-process analytics database for fast local OLAP.
How Orbit entities map to DuckDB
| Orbit entity | DuckDB object | Notes |
|---|---|---|
| members | orbit_members | id PK · custom fields → JSON or STRUCT columns |
| activities | orbit_activities | TIMESTAMP WITH TIME ZONE events |
| organizations | orbit_organizations | id PK · linked to orbit_members |
| love scores | orbit_love_scores | id PK · linked to orbit_members |
FAQ
How does Datrise handle Orbit'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 Orbit 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
More destinations for Orbit
Early access
Connect Orbit to DuckDB the easy way
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