DatriseAI-first ETL

Codat to Amazon Redshift Integration

AI-first ETL from Codat into Amazon Redshift. Governed entities, incremental sync, typed landing tables.

How Datrise loads Codat into Amazon Redshift

Datrise syncs Codat's companies, accounts, invoices, bills, journal entries, and payments into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.

Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.

Ideal for AWS-native warehouses already using the Redshift ecosystem.

Endpoints

Codat: Unified API for accounting and banking data.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Codat entities map to Amazon Redshift

Codat entityAmazon Redshift objectNotes
companiescodat_companiesid PK · custom fields → SUPER columns
accountscodat_accountsid PK · linked to codat_companies
invoicescodat_invoicesid PK · linked to codat_companies
billscodat_billsid PK · linked to codat_companies

FAQ

How does Datrise handle Codat's custom fields in Amazon Redshift?

Flexible values are stored as SUPER columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Redshift types.

How does the Codat to Amazon Redshift sync stay up to date?

It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.

Related pipelines

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