DatriseAI-first ETL

Buildertrend Snowflake

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

How Datrise loads Buildertrend into Snowflake

Datrise syncs Buildertrend's contacts, accounts, deals, activities, and lifecycle events 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

Buildertrend: Construction CRM for jobs, estimates, and contractor pipelines.

Snowflake: Cloud data warehouse with separated compute and storage.

How Buildertrend entities map to Snowflake

Buildertrend entitySnowflake objectNotes
contactsbuildertrend_contactsid PK · custom fields → VARIANT columns
accountsbuildertrend_accountsid PK · linked to buildertrend_contacts
dealsbuildertrend_dealsid PK · linked to buildertrend_contacts
activitiesbuildertrend_activitiesTIMESTAMP_TZ events

FAQ

How does Datrise handle Buildertrend'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 Buildertrend 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

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