Documentation Data Sources FAQs

Data source swaps and migrations

There may come a time where you want to switch the data source your charts and dashboards are connected to from one data source to another. The complexity of this switch depends on several factors, so we recommend reaching out to us at to discuss implications in Chartio.

Note: If your data source switch requires excessive assistance from us, there may be additional services fees involved.

  • If you’re moving your data to a data source of the same type as the original, this is called a data source swap.
  • If you’re moving your data to a data source of a different type, this is called a data source migration. This scenario requires you to consider and take action on several factors before migration can take place.


Before we perform a data source swap or migration, you’ll first need to ensure the following conditions are met:

  • Confirm all the tables and fields in your new data source are named exactly the same (case-sensitive) as the original, including any custom tables or columns.
  • All tables and columns must have the same naming conventions.
  • Clone a dashboard using the original data source. We’ll first attempt the swap/migration on the cloned dashboard before attempting a full swap/migration.

Google Sheets prerequisite

If you’d like us to perform a data source swap between two Google Sheets, you’ll also need to confirm the Google Sheets both have the same name and title, in addition to the other prerequisites listed above. Once confirmed, we can attempt the data source swap.

Data source swap

If you’re switching to a database with the same underlying type as the original database (e.g., Redshift to Redshift), this is called a data source swap. So you don’t need to recreate any charts, we can perform a data source swap for your charts, dashboards, and data stores from the backend. Before requesting a data source swap, please make sure all the prerequisites are met before reaching out to us.

To request a data source swap, contact us at

Data source migration

If you’re switching to a database with a different underlying type compared to the original database (e.g., Redshift to Snowflake), this is called a data source migration.

All the prerequisites still apply to a data source migration, but additional issues arise when the two data sources have fundamental differences between their syntax, logic, and supported functions. Some implications include the following:

  • Different database types may not have identical SQL syntax, including functions that may not be supported in the new database. As a result, SQL mode charts may break and you will need to update your charts.
  • Different database types may produce column names in different cases. For example, PostgreSQL queries will only capitalize the first letter of a column (e.g., “User Count”), but Redshift generates all columns in lowercase (e.g., “user count”) and Snowflake’s schema is in all caps (e.g., “USER COUNT”). This will break your charts that have Hide Column or Rename Column steps in the Pipeline because they reference the original columns. You’ll need to fix these charts after the migration by selecting the proper columns in the Pipeline.

This is a much more involved process and impacts many parts of Chartio, including your original Visual Mode and SQL Mode queries and subsequent pipeline steps. To learn more about data source migrations, contact us at

There are a few companies that assist in migration consulting (reach out to us if you’d like an introduction). While they can assist with some of the steps, we’ve found that a migration will require a fair amount of manual work by your team.