DatriseAI-first ETL

Drift to Redash Integration

AI-first ETL from Drift into Redash. Governed entities, incremental sync, typed landing tables.

How Datrise loads Drift into Redash

Datrise syncs Drift's conversations, contacts, playbooks, meetings, messages, and accounts into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

Drift: Conversational marketing and sales chat.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Drift entities map to Redash

Drift entityRedash objectNotes
conversationsdrift_conversationsid PK · custom fields → flattened columns for query results
contactsdrift_contactsid PK · linked to drift_conversations
playbooksdrift_playbooksid PK · linked to drift_conversations
meetingsdrift_meetingsid PK · linked to drift_conversations

FAQ

How does Datrise handle Drift's custom fields in Redash?

Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.

How does the Drift to Redash sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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