kvCORE → Mode
AI-first ETL from kvCORE into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads kvCORE into Mode
Datrise syncs kvCORE'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
kvCORE: Real estate CRM for leads, listings, and agent follow-up.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How kvCORE entities map to Mode
| kvCORE entity | Mode object | Notes |
|---|---|---|
| contacts | kvcore_contacts | id PK · custom fields → flattened columns for SQL and notebooks |
| accounts | kvcore_accounts | id PK · linked to kvcore_contacts |
| deals | kvcore_deals | id PK · linked to kvcore_contacts |
| activities | kvcore_activities | temporal columns events |
FAQ
How does Datrise handle kvCORE'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 kvCORE to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for kvCORE
Early access
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