DatriseAI-first ETL

Smartsheet to Snowflake Integration

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

How Datrise loads Smartsheet into Snowflake

Datrise syncs Smartsheet's sheets, rows, columns, cells, attachments, and comments 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

Smartsheet: Spreadsheet-style work and project management.

Snowflake: Cloud data warehouse with separated compute and storage.

How Smartsheet entities map to Snowflake

Smartsheet entitySnowflake objectNotes
sheetssmartsheets_sheetsid PK · custom fields → VARIANT columns
rowssmartsheets_rowsid PK · linked to smartsheets_sheets
columnssmartsheets_columnsid PK · linked to smartsheets_sheets
cellssmartsheets_cellsid PK · linked to smartsheets_sheets

FAQ

How does Datrise handle Smartsheet'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 Smartsheet 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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