DatriseAI-first ETL

Formkeep to Databricks SQL Warehouse Integration

AI-first ETL from Formkeep into Databricks SQL Warehouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Formkeep into Databricks SQL Warehouse

Datrise syncs Formkeep's forms, submissions, fields, answers, spam flags, and notifications into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

Formkeep: Hosted form endpoints and submission storage.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Formkeep entities map to Databricks SQL Warehouse

Formkeep entityDatabricks SQL Warehouse objectNotes
formsformkeep_formsid PK · custom fields → VARIANT or STRUCT columns
submissionsformkeep_submissionsid PK · linked to formkeep_forms
fieldsformkeep_fieldsid PK · linked to formkeep_forms
answersformkeep_answersid PK · linked to formkeep_forms

FAQ

How does Datrise handle Formkeep's custom fields in Databricks SQL Warehouse?

Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.

How does the Formkeep to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

Early access

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