DatriseAI-first ETL

Zoho CRM DuckDB

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

How Datrise loads Zoho CRM into DuckDB

Datrise syncs Zoho CRM's leads, contacts, accounts, deals, and workflow-driven field changes 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

Zoho CRM: Modular CRM with strong automation and telephony.

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

How Zoho CRM entities map to DuckDB

Zoho CRM entityDuckDB objectNotes
leadszoho_crm_leadsid PK · custom fields → JSON or STRUCT columns
contactszoho_crm_contactsid PK · linked to zoho_crm_leads
accountszoho_crm_accountsid PK · linked to zoho_crm_leads
dealszoho_crm_dealsid PK · linked to zoho_crm_leads

FAQ

How does Datrise handle Zoho 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 Zoho 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.

Related pipelines

Early access

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