Front to Amazon Redshift Integration

How Datrise loads Front into Amazon Redshift

Datrise syncs Front's conversations, messages, contacts, inboxes, tags, and teammates 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

Front: Shared inbox for team email and messaging.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Front entities map to Amazon Redshift

Front entity	Amazon Redshift object	Notes
conversations	`frontapp_conversations`	id PK · custom fields → SUPER columns
messages	`frontapp_messages`	id PK · linked to frontapp_conversations
contacts	`frontapp_contacts`	id PK · linked to frontapp_conversations
inboxes	`frontapp_inboxes`	id PK · linked to frontapp_conversations

FAQ

How does Datrise handle Front'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 Front 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

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