Resolving the ‘Authentication Type 10 Not Supported’ Error for Amazon QuickSight and Amazon RDS

Overview

In the realm of data analysis and visualization, tools like Amazon QuickSight and databases like Amazon RDS play crucial roles. However, sometimes, connecting these services can lead to unexpected errors, such as the ‘Authentication Type 10 Not Supported’ error. This error can disrupt your workflow and hinder your ability to access and analyze your data effectively. In this blog, we’ll dive into the common causes of this error and provide simple solutions to troubleshoot and resolve it, ensuring smooth connectivity between Amazon QuickSight and Amazon RDS for seamless data analysis experiences.

Introduction

On the other hand, Amazon RDS offers a managed database service, simplifying the setup, operation, and scaling of relational databases. Together, these services form a robust foundation for businesses to analyze their data effectively and make informed decisions.

Understanding the Error

Error Details: When attempting to connect Amazon QuickSight with Amazon RDS, users might encounter the following error message:

Underlying Causes of the Error

The errors happen because the way passwords are encrypted in newer versions of PostgreSQL has changed to something called SCRAM authentication. QuickSight uses a driver to connect, which doesn’t support the new encryption method “scram-sha-256”; it only supports the older “md5” encryption.

Before PostgreSQL 14, SCRAM authentication existed from version 10 onwards, but it wasn’t a problem for most because it wasn’t the default. It was something you had to choose to use. Now, with PostgreSQL 14, things are changing. Older versions are not supported anymore, and there’s a push for everyone to upgrade. This means old ways of encrypting passwords are replaced by SCRAM authentication, making it the primary method.

SCRAM Authentication

This approach is tough against:

• Guessing passwords from a list
• Repeating previously captured login data
• Stealing stored password codes

In summary, it makes breaking into an account with a password much more difficult.

Steps to Resolve the Authentication Error

To make sure new passwords are encrypted in a certain way in your RDS database, you can create a custom parameter group. Choose the family as aurora-postgresql14 and the type as DB Cluster Parameter group. Set a parameter called password_encryption to ‘md5’ in this group. Then, connect this parameter group to your cluster and restart the cluster so that the new settings apply.

After doing this, any new passwords you set will be encrypted using ‘md5’. But remember, the existing passwords will stick with the old encryption. If you want to update the encryption for those, you’ll need to change the password for the main user of the database.

Step 1: Create an Amazon RDS custom parameter group by selecting the parameter group family as aurora-postgresql14, and the type will be DB Cluster Parameter group.

Step 2: Once created, Edit the Parameter group, set password_encryption  to ‘md5’, and save it.

Step 3: Select the Amazon RDS Database cluster. Click on modify and attach it to the cluster of the Amazon RDS database.

Step 4: Select the option “Apply Immediately” and save it.

Note – It will require a reboot. The changes are applied immediately

Step 5: Connect to the Amazon RDS Database and Update the password of the database master user

Command: ALTER USER postgres WITH PASSWORD ‘<enter your password here>’

Note: Any existing password will still be encrypted using previous encryption, and the new password will be encrypted using ‘md5’.

Conclusion

Following the step-by-step solutions outlined in this guide, you can overcome the ‘Authentication Type 10 Not Supported’ error and establish a successful connection between Amazon QuickSight and Amazon RDS. Streamlining this process ensures a smoother experience and unlocks the full potential of your data visualization and analysis.

Drop a query if you have any questions regarding Authentication Error and we will get back to you quickly.

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