Secoda to DuckDB Integration
AI-first ETL from Secoda into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Secoda into DuckDB
Datrise syncs Secoda's tables, columns, dictionaries, lineage edges, owners, and documentation entries 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
Secoda: Data catalog, lineage, and documentation.
DuckDB: In-process analytics database for fast local OLAP.
How Secoda entities map to DuckDB
| Secoda entity | DuckDB object | Notes |
|---|---|---|
| tables | secoda_tables | id PK · custom fields → JSON or STRUCT columns |
| columns | secoda_columns | id PK · linked to secoda_tables |
| dictionaries | secoda_dictionaries | id PK · linked to secoda_tables |
| lineage edges | secoda_lineage_edges | id PK · linked to secoda_tables |
FAQ
How does Datrise handle Secoda'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 Secoda 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 Secoda
Early access
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