DatriseAI-first ETL

Persistiq to Amazon Redshift Integration

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

How Datrise loads Persistiq into Amazon Redshift

Datrise syncs Persistiq's prospects, campaigns, sequences, email events, users, and dispositions 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

Persistiq: Outbound sales sequences and prospect tracking.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Persistiq entities map to Amazon Redshift

Persistiq entityAmazon Redshift objectNotes
prospectspersistiq_prospectsid PK · custom fields → SUPER columns
campaignspersistiq_campaignsid PK · linked to persistiq_prospects
sequencespersistiq_sequencesid PK · linked to persistiq_prospects
email eventspersistiq_email_eventsTIMESTAMPTZ events

FAQ

How does Datrise handle Persistiq'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 Persistiq 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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