Apollo → PostgreSQL
AI-first ETL from Apollo into PostgreSQL. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apollo into PostgreSQL
Datrise syncs Apollo's sales intelligence records, account engagement, and outbound activity into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.
Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.
Ideal for operational analytics and application backends that need fresh, queryable copies of your data.
Endpoints
Apollo: Sales intelligence and engagement platform with account-level activity.
PostgreSQL: Open-source relational database with strong SQL and extensions.
How Apollo entities map to PostgreSQL
| Apollo entity | PostgreSQL object | Notes |
|---|---|---|
| sales intelligence records | apollo_sales_intelligence_records | id PK · custom fields → jsonb columns |
| account engagement | apollo_account_engagement | id PK · linked to apollo_sales_intelligence_records |
| outbound activity | apollo_outbound_activity | timestamptz events |
FAQ
How does Datrise handle Apollo's custom fields in PostgreSQL?
Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PostgreSQL types.
How does the Apollo to PostgreSQL sync stay up to date?
It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.
Related pipelines
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Early access
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