DatriseAI-first ETL

Codat to ClickHouse Integration

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

How Datrise loads Codat into ClickHouse

Datrise syncs Codat's companies, accounts, invoices, bills, journal entries, and payments into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.

Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.

Ideal for high-volume event analytics that need sub-second aggregation.

Endpoints

Codat: Unified API for accounting and banking data.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Codat entities map to ClickHouse

Codat entityClickHouse objectNotes
companiescodat_companiesid PK · custom fields → JSON or Map 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 ClickHouse?

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

How does the Codat to ClickHouse sync stay up to date?

It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.

Related pipelines

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