Nectar CRM to DuckDB Integration
AI-first ETL from Nectar CRM into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Nectar CRM into DuckDB
Datrise syncs Nectar CRM's contacts, companies, opportunities, sales stages, activities, and quotes 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
Nectar CRM: B2B sales CRM with playbooks for Brazilian teams.
DuckDB: In-process analytics database for fast local OLAP.
How Nectar CRM entities map to DuckDB
| Nectar CRM entity | DuckDB object | Notes |
|---|---|---|
| contacts | nectar_crm_contacts | id PK · custom fields → JSON or STRUCT columns |
| companies | nectar_crm_companies | id PK · linked to nectar_crm_contacts |
| opportunities | nectar_crm_opportunities | id PK · linked to nectar_crm_contacts |
| sales stages | nectar_crm_sales_stages | id PK · linked to nectar_crm_contacts |
FAQ
How does Datrise handle Nectar CRM'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 Nectar CRM to DuckDB sync stay up to date?
It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.
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