Chartmogul → PostgreSQL
AI-first ETL from Chartmogul into PostgreSQL. Governed entities, incremental sync, typed landing tables.
How Datrise loads Chartmogul into PostgreSQL
Datrise syncs Chartmogul's records, events, and configuration objects 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
Chartmogul: SaaS or API data source for analytics and warehouse sync.
PostgreSQL: Open-source relational database with strong SQL and extensions.
How Chartmogul entities map to PostgreSQL
| Chartmogul entity | PostgreSQL object | Notes |
|---|---|---|
| records | chartmogul_records | id PK · custom fields → jsonb columns |
| events | chartmogul_events | timestamptz events |
| configuration objects | chartmogul_configuration_objects | id PK · linked to chartmogul_records |
FAQ
How does Datrise handle Chartmogul'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 Chartmogul 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
More destinations for Chartmogul
- Chartmogul → MySQL
- Chartmogul → Microsoft SQL Server
- Chartmogul → Oracle Database
- Chartmogul → Snowflake
- Chartmogul → Google BigQuery
- Chartmogul → Amazon Redshift
- Chartmogul → Databricks SQL Warehouse
- Chartmogul → ClickHouse
- Chartmogul → DuckDB
- Chartmogul → Amazon Athena
- Chartmogul → Amazon S3 Data Lake
- Chartmogul → Azure Data Lake Storage
Early access
Connect Chartmogul to PostgreSQL the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.