DatriseAI-first ETL

Agendor to Snowflake Integration

AI-first ETL from Agendor into Snowflake. Governed entities, incremental sync, typed landing tables.

How Datrise loads Agendor into Snowflake

Datrise syncs Agendor's organizations, people, deals, funnel stages, activities, and proposals into Snowflake as a typed table per source entity. Flexible or custom fields land in VARIANT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP_TZ.

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

Agendor: Brazilian sales CRM for pipeline and account follow-up.

Snowflake: Cloud data warehouse with separated compute and storage.

How Agendor entities map to Snowflake

Agendor entitySnowflake objectNotes
organizationsagendor_organizationsid PK · custom fields → VARIANT columns
peopleagendor_peopleid PK · linked to agendor_organizations
dealsagendor_dealsid PK · linked to agendor_organizations
funnel stagesagendor_funnel_stagesid PK · linked to agendor_organizations

FAQ

How does Datrise handle Agendor's custom fields in Snowflake?

Flexible values are stored as VARIANT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Snowflake types.

How does the Agendor to Snowflake sync stay up to date?

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

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