Your Location Data Services credits
Understand how credits for Location Data Services work.
Why do you need this?
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You use services like geocoding, isolines and routing frequently and want to understand how your monthly credit quotas work.
What are Location Data Services?
Location Data Services are mainly a set of services that can be used to perform certain operations on your data (eg: geocoding, calculating routes, etc.). They can be used via the Data Services API. Some of these services are also available in the form of Builder analyses (eg: geocoding by city name, travel buffer, etc).
What are credits?
As a CARTO user, you have a certain monthly quota of credits for Location Data Services (LDS) depending on your account type (12-month free account, Individual plan or the different Enterprise plans). If you run out of credits, you will have to wait to use LDS until the beginning of the next quota cycle (when you first signed up) when your credits refresh. Enterprise users can purchase additional credits anytime.
What are the services that consume credits?
How many credits are consumed when using Location Data Services?
The number of credits consumed is directly proportional to the number of resulting rows. For example, if a table with 100 rows is geocoded by street address, 100 credits will be consumed. Similarly, if you run a query that generates 2 isolines, 2 credits will be consumed.
Results are not cached. Avoid running dynamic queries to these functions in your maps. This can result in credit consumption per map view.
How can you check the number of credits used/left for each service in your monthly quota?
In your Dashboard
At any given moment, you can check the status of your monthly credit quotas in your Dashboard. Here, you will be able to check, for each service, the total number of credits you have available every month, as well as the number of credits you have currently used and have available.
Programmatically
There are several SQL functions to check the actual usage of each of these services programmatically (eg: using the SQL API).