DatriseAI-first ETL

Real Geeks Amazon Redshift

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

How Datrise loads Real Geeks into Amazon Redshift

Datrise syncs Real Geeks'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

Real Geeks: Real estate CRM for leads, listings, and agent follow-up.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Real Geeks entities map to Amazon Redshift

Real Geeks entityAmazon Redshift objectNotes
contactsreal_geeks_contactsid PK · custom fields → SUPER columns
accountsreal_geeks_accountsid PK · linked to real_geeks_contacts
dealsreal_geeks_dealsid PK · linked to real_geeks_contacts
activitiesreal_geeks_activitiesTIMESTAMPTZ events

FAQ

How does Datrise handle Real Geeks'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 Real Geeks 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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