Gong to Snowflake Integration

How Datrise loads Gong into Snowflake

Datrise syncs Gong's calls, transcripts, deals, users, trackers, and call topics 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

Gong: Revenue intelligence from recorded sales calls.

Snowflake: Cloud data warehouse with separated compute and storage.

How Gong entities map to Snowflake

Gong entity	Snowflake object	Notes
calls	`gong_calls`	id PK · custom fields → VARIANT columns
transcripts	`gong_transcripts`	id PK · linked to gong_calls
deals	`gong_deals`	id PK · linked to gong_calls
users	`gong_users`	id PK · linked to gong_calls

FAQ

How does Datrise handle Gong'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 Gong 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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