DatriseAI-first ETL

Visma e-conomic to ClickHouse Integration

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

How Datrise loads Visma e-conomic into ClickHouse

Datrise syncs Visma e-conomic's invoices, customers, suppliers, journal entries, accounts, and products 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

Visma e-conomic: Nordic accounting, invoicing, and ledger records.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Visma e-conomic entities map to ClickHouse

Visma e-conomic entityClickHouse objectNotes
invoicesvisma_e_conomic_invoicesid PK · custom fields → JSON or Map columns
customersvisma_e_conomic_customersid PK · linked to visma_e_conomic_invoices
suppliersvisma_e_conomic_suppliersid PK · linked to visma_e_conomic_invoices
journal entriesvisma_e_conomic_journal_entriesid PK · linked to visma_e_conomic_invoices

FAQ

How does Datrise handle Visma e-conomic'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 Visma e-conomic 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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