DatriseAI-first ETL

Megaplan PostgreSQL

AI-first ETL from Megaplan into PostgreSQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Megaplan into PostgreSQL

Datrise syncs Megaplan's contacts, accounts, deals, activities, and lifecycle events into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Megaplan: CRM with strong adoption in CIS markets for sales and operations.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Megaplan entities map to PostgreSQL

Megaplan entityPostgreSQL objectNotes
contactsmegaplan_contactsid PK · custom fields → jsonb columns
accountsmegaplan_accountsid PK · linked to megaplan_contacts
dealsmegaplan_dealsid PK · linked to megaplan_contacts
activitiesmegaplan_activitiestimestamptz events

FAQ

How does Datrise handle Megaplan's custom fields in PostgreSQL?

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

How does the Megaplan to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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