How it works
ChartMogul writes the data as Parquet files to an Amazon S3 or Google Cloud Storage bucket you own, then loads them into a Snowflake schema (chartmogul_data by default). Each load replaces the previous tables.
Connecting. You run a short SQL script in Snowflake that creates a database, a small warehouse, a role, a network policy, and a service user. ChartMogul connects as that user with key-pair authentication. You need ACCOUNTADMIN in Snowflake.
Before you connect
- Snowflake is phasing out password-only sign-in, so destinations set up with a password need to switch to key-pair authentication.
- Data already synced stays in Snowflake if you delete the destination.
Setting it up
In ChartMogul, go to Settings > Destinations and add Snowflake. The Snowflake guide walks through each step.
What ChartMogul exports
Every warehouse and storage destination gets the same two sets of tables.
Your source data
Customers, custom attributes, tags, contacts and their custom attributes, invoices and line items, transactions, subscription events, plans, opportunities and their custom attributes, notes and call logs, tasks, currency rates, and data sources.
ChartMogul’s calculations
Customers with their MRR, ARR, and status, subscriptions, MRR and CMRR movements, MRR per customer per month, MRR and quantity per customer per month per plan, MRR intervals, and plan groups.
When it runs
Daily, weekly, or monthly, and you can also send data on demand. Field-level schemas are in the developer docs.