Lofty → Redash
AI-first ETL from Lofty into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads Lofty into Redash
Datrise syncs Lofty's contacts, accounts, deals, activities, and lifecycle events 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
Lofty: Real estate CRM for leads, listings, and agent follow-up.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How Lofty entities map to Redash
| Lofty entity | Redash object | Notes |
|---|---|---|
| contacts | lofty_contacts | id PK · custom fields → flattened columns for query results |
| accounts | lofty_accounts | id PK · linked to lofty_contacts |
| deals | lofty_deals | id PK · linked to lofty_contacts |
| activities | lofty_activities | temporal columns events |
FAQ
How does Datrise handle Lofty'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 Lofty to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
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