Real Geeks → Mode
AI-first ETL from Real Geeks into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads Real Geeks into Mode
Datrise syncs Real Geeks's contacts, accounts, deals, activities, and lifecycle events into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
Real Geeks: Real estate CRM for leads, listings, and agent follow-up.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How Real Geeks entities map to Mode
| Real Geeks entity | Mode object | Notes |
|---|---|---|
| contacts | real_geeks_contacts | id PK · custom fields → flattened columns for SQL and notebooks |
| accounts | real_geeks_accounts | id PK · linked to real_geeks_contacts |
| deals | real_geeks_deals | id PK · linked to real_geeks_contacts |
| activities | real_geeks_activities | temporal columns events |
FAQ
How does Datrise handle Real Geeks's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the Real Geeks to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
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