DatriseAI-first ETL

Wise Agent Amazon Redshift

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

How Datrise loads Wise Agent into Amazon Redshift

Datrise syncs Wise Agent'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

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

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Wise Agent entities map to Amazon Redshift

Wise Agent entityAmazon Redshift objectNotes
contactswise_agent_contactsid PK · custom fields → SUPER columns
accountswise_agent_accountsid PK · linked to wise_agent_contacts
dealswise_agent_dealsid PK · linked to wise_agent_contacts
activitieswise_agent_activitiesTIMESTAMPTZ events

FAQ

How does Datrise handle Wise Agent'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 Wise Agent 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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