Codat to DuckDB Integration
AI-first ETL from Codat into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Codat into DuckDB
Datrise syncs Codat's companies, accounts, invoices, bills, journal entries, and payments 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
Codat: Unified API for accounting and banking data.
DuckDB: In-process analytics database for fast local OLAP.
How Codat entities map to DuckDB
| Codat entity | DuckDB object | Notes |
|---|---|---|
| companies | codat_companies | id PK · custom fields → JSON or STRUCT columns |
| accounts | codat_accounts | id PK · linked to codat_companies |
| invoices | codat_invoices | id PK · linked to codat_companies |
| bills | codat_bills | id PK · linked to codat_companies |
FAQ
How does Datrise handle Codat'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 Codat 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 Codat
Early access
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