In this example, a fictional fish tank health vendor uses InfluxDB 2.0 Alpha 15's SQL.to() functionality to write data from Flux results into a Postgres database for storing customer billing data. The vendor leverages Flux to collect and process data on corrective actions taken by automated water systems in their customers' tanks, which are stored in InfluxDB as time series events. However, the aggregated and processed data represents a "finished product" that is more suitable for storage with other customer data, such as billing address and telephone number, in a relational database like Postgres. The vendor creates a simple weekly task to count adjustments for each device and save them to their Postgres database using Flux, demonstrating the power and flexibility of multi-data source Flux.