DatriseAI-first ETL

Megaplan Amazon Redshift

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

How Datrise loads Megaplan into Amazon Redshift

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

Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.

Ideal for AWS-native warehouses already using the Redshift ecosystem.

Endpoints

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

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Megaplan entities map to Amazon Redshift

Megaplan entityAmazon Redshift objectNotes
contactsmegaplan_contactsid PK · custom fields → SUPER 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 Amazon Redshift?

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

How does the Megaplan to Amazon Redshift sync stay up to date?

It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.

Related pipelines

Early access

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