DatriseAI-first ETL

NetSuite ClickHouse

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

How Datrise loads NetSuite into ClickHouse

Datrise syncs NetSuite's transactions, customers, items, subsidiaries, and GL activity 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

NetSuite: Cloud ERP for finance, inventory, and operations.

ClickHouse: Columnar OLAP engine for fast aggregations.

How NetSuite entities map to ClickHouse

NetSuite entityClickHouse objectNotes
transactionsnetsuite_transactionsid PK · custom fields → JSON or Map columns
customersnetsuite_customersid PK · linked to netsuite_transactions
itemsnetsuite_itemsid PK · linked to netsuite_transactions
subsidiariesnetsuite_subsidiariesid PK · linked to netsuite_transactions

FAQ

How does Datrise handle NetSuite'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 NetSuite 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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