Trello → DuckDB
AI-first ETL from Trello into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Trello into DuckDB
Datrise syncs Trello's boards, lists, cards, members, and activity logs 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
Trello: Kanban boards for tasks and lightweight project tracking.
DuckDB: In-process analytics database for fast local OLAP.
How Trello entities map to DuckDB
| Trello entity | DuckDB object | Notes |
|---|---|---|
| boards | trello_boards | id PK · custom fields → JSON or STRUCT columns |
| lists | trello_lists | id PK · linked to trello_boards |
| cards | trello_cards | id PK · linked to trello_boards |
| members | trello_members | id PK · linked to trello_boards |
FAQ
How does Datrise handle Trello'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 Trello 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 Trello
Early access
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