Megaplan → Chartio
AI-first ETL from Megaplan into Chartio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Megaplan into Chartio
Datrise syncs Megaplan's contacts, accounts, deals, activities, and lifecycle events into Chartio as SQL tables a visual-SQL explorer connects to. Flexible or custom fields land in flattened columns for visual SQL, 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. Visual-SQL tools build joins from your schema, so Datrise lands clearly related tables with stable id columns.
Ideal for drag-and-drop charting over a database.
Endpoints
Megaplan: CRM with strong adoption in CIS markets for sales and operations.
Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.
How Megaplan entities map to Chartio
| Megaplan entity | Chartio object | Notes |
|---|---|---|
| contacts | megaplan_contacts | id PK · custom fields → flattened columns for visual SQL |
| accounts | megaplan_accounts | id PK · linked to megaplan_contacts |
| deals | megaplan_deals | id PK · linked to megaplan_contacts |
| activities | megaplan_activities | temporal columns events |
FAQ
How does Datrise handle Megaplan's custom fields in Chartio?
Flexible values are stored as flattened columns for visual SQL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Chartio types.
How does the Megaplan to Chartio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Megaplan
Early access
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