Optimizing your data

When you open a table in Data Explorer, CARTO will analyze the table to check for any possible performance optimization, based on our performance considerations for geospatial analysis.

If we detect a performance optimization, you will see a banner above the preview, similar to this one:

This is a table that wasn't clustered based on geospatial data. Clustering on geospatial data might improve performance and save costs

After you click on "Optimize this table", there are two scenarios depending on the type of optimization:

• Automatic optimizations: CARTO will automatically update the table

• Create an optimized table: CARTO will copy the table, and the new one will be optimized. We'll ask you to select where you want to store the optimized table, and you can select a different name than the default `_optimized` suffix.

After you request any optimization, you'll see your optimization job running in the header, and the table preview will also update as soon as the optimization job has finished.

For Databricks connections, your Databricks workspace needs to be enabled with Spatial SQL functions, which are currently in Private Preview. The Databricks team has made this form available to request access to the functions. Please get in touch with them through the form to gain access to all Spatial SQL functions.

All the optimizations are non-destructive, meaning they don't alter the data in any sensible way order than sorting, clustering, column-formatting, or enabling systems available for each connection (such as Search Optimization Service for Snowflake).

To understand what each optimization does in detail, read our performance considerations guide.

After you're done, your optimized table will perform better in most scenarios, and in the long run, it should lower your computing costs.

In most cases, we recommend you delete the original table and rename the new one, to keep your database clean and tidy.