DatriseAI-first ETL

NetSuite DuckDB

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

How Datrise loads NetSuite into DuckDB

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

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

DuckDB: In-process analytics database for fast local OLAP.

How NetSuite entities map to DuckDB

NetSuite entityDuckDB objectNotes
transactionsnetsuite_transactionsid PK · custom fields → JSON or STRUCT 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 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 NetSuite 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

Early access

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