DatriseAI-first ETL

Salesflare Snowflake

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

How Datrise loads Salesflare into Snowflake

Datrise syncs Salesflare's B2B account intelligence, interactions, and automated relationship timelines 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

Salesflare: B2B CRM focused on automation and relationship timeline data.

Snowflake: Cloud data warehouse with separated compute and storage.

How Salesflare entities map to Snowflake

Salesflare entitySnowflake objectNotes
B2B account intelligencesalesflare_b2b_account_intelligenceid PK · custom fields → VARIANT columns
interactionssalesflare_interactionsid PK · linked to salesflare_b2b_account_intelligence
automated relationship timelinessalesflare_automated_relationship_timelinesTIMESTAMP_TZ events

FAQ

How does Datrise handle Salesflare'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 Salesflare 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.

Related pipelines

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