DatriseAI-first ETL

Primetric to Snowflake Integration

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

How Datrise loads Primetric into Snowflake

Datrise syncs Primetric's projects, assignments, people, timesheets, budgets, and utilization rates 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

Primetric: Project profitability and resource forecasting.

Snowflake: Cloud data warehouse with separated compute and storage.

How Primetric entities map to Snowflake

Primetric entitySnowflake objectNotes
projectsprimetric_projectsid PK · custom fields → VARIANT columns
assignmentsprimetric_assignmentsid PK · linked to primetric_projects
peopleprimetric_peopleid PK · linked to primetric_projects
timesheetsprimetric_timesheetsid PK · linked to primetric_projects

FAQ

How does Datrise handle Primetric'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 Primetric 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

Early access

Connect Primetric to Snowflake the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.