How it works
ChartMogul writes the data as Parquet files to an Amazon S3 bucket you own, then loads them into a Redshift schema it creates. Each load replaces the previous tables.
Connecting. You give ChartMogul your cluster's host, port, database, and a user, plus an S3 bucket and an IAM user that can write to it.
Before you connect
- The cluster must be publicly accessible, with a security group that only allows ChartMogul's IP addresses.
- Use a separate bucket if you already send ChartMogul data to S3.
Setting it up
In ChartMogul, go to Settings > Destinations and add Amazon Redshift. The Amazon Redshift 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.