Source connector
ChartMogul connector
ChartMogul integration for databases, warehouses and BI tools
Subscription analytics and revenue reporting. Datrise captures ChartMogul entities such as customers, subscriptions, invoices, MRR movements, plans and churn events, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.
Of the 6 objects, 4 sync as upserts keyed on the primary key and 2 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `chartmogul_customers`) with a schema derived from the ChartMogul API rather than a flattened CSV, in any of the 43 supported destinations.
Datrise is in early access: pick a destination below to open the ChartMogul pipeline page, and join the waitlist to get the ChartMogul connector with guided onboarding.
What ChartMogul data Datrise extracts
Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.
| Object | Landing table | Sync mode |
|---|---|---|
| customers | chartmogul_customers | Upsert by primary key, incremental on updated-at |
| subscriptions | chartmogul_subscriptions | Upsert by primary key, incremental on updated-at |
| invoices | chartmogul_invoices | Append-only, incremental by timestamp |
| MRR movements | chartmogul_mrr_movements | Upsert by primary key, incremental on updated-at |
| plans | chartmogul_plans | Upsert by primary key, incremental on updated-at |
| churn events | chartmogul_churn_events | Append-only, incremental by timestamp |
Popular destinations for ChartMogul
Choose a destination below to open the ready pipeline page.
- AAirtable
Relational spreadsheet destination for ops and go-to-market teams.
View pipeline - AAmazon Athena
Serverless SQL over S3 data lake tables.
View pipeline - AAmazon DynamoDB
Serverless key-value and document store on AWS.
View pipeline - AAmazon QuickSight
AWS serverless BI with SPICE and embedded analytics.
View pipeline - AAmazon Redshift
AWS petabyte-scale warehouse with Spectrum.
View pipeline - AAmazon S3 Data Lake
Object storage landing zone for parquet and snapshots.
View pipeline - AApache Superset
Open-source BI for SQL exploration, charts, and dashboard publishing.
View pipeline - AAzure Data Lake Storage
ADLS Gen2 object storage for analytics workloads.
View pipeline - AAzure Synapse
Microsoft analytics workspace with SQL pools.
View pipeline
ChartMogul connector FAQ
- What ChartMogul data does the connector extract?
- 6 objects: customers, subscriptions, invoices, MRR movements, plans and churn events. Each lands in its own table with types preserved; history-style objects (2: invoices and churn events) load as append-only streams.
- Is the ChartMogul integration incremental?
- Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
- Where can I load ChartMogul data?
- Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each ChartMogul → destination pair has its own page with the object-to-table mapping.
Related sources
Other sources in the same category, each with its own connector page.
Early access
Launch your ChartMogul pipeline with guided onboarding
Join the waitlist to get priority access for ChartMogul integrations with guided setup, schema-aware mapping, and production-grade incremental sync.