[Update] I tried out Amazon SageMaker Unified Studio's new support for Amazon OpenSearch Service as a data source

This is Ishikawa from the Cloud Business Headquarters. Amazon SageMaker Unified Studio now supports Amazon OpenSearch Service as a data source. You can now directly query and analyze search data and log analysis data on OpenSearch alongside other data assets such as Amazon Redshift and Amazon S3, all within a single governed environment.

https://aws.amazon.com/jp/about-aws/whats-new/2026/07/amazon-sagemaker-unified/

For those who have been switching between separate tools to handle operational search/log data and analytical structured data, this is a welcome update that enables cross-source analysis without having to switch tools.

What is Amazon SageMaker Unified Studio

Amazon SageMaker Unified Studio is an integrated development environment provided as part of the next-generation Amazon SageMaker. It consolidates AWS data, analytics, and AI/machine learning (ML) services into a single interface, allowing you to build, deploy, run, and monitor workflows from one place. Since data and compute resources can be shared among team members on a per-project basis, it supports collaboration across teams and agile development.

What's New

With this update, you can now connect Amazon OpenSearch Service as a data source in Amazon SageMaker Unified Studio.

The main changes are as follows:

• Amazon OpenSearch Service can now be added as a project data source (while the title states "... now supports Amazon OpenSearch," Amazon OpenSearch Serverless is not included)
• Connected OpenSearch data is displayed alongside other project data in the data explorer
• Direct querying in the query editor, exploration in notebooks, and integration into visual ETL jobs are all supported
• OpenSearch operational search data can be combined and analyzed together with data from Amazon Redshift, Amazon S3, relational databases, and more, all within a single governed environment

This integration is especially valuable when you want to correlate data across analytical and operational workloads. For example, by joining application logs and metrics stored in OpenSearch with transaction data, you can gain insights into system performance and user behavior.

Data engineers and analysts can build data pipelines that handle real-time search/analytics data and structured datasets together, streamlining cross-source workflows without switching tools.

Supported Regions

Available in all AWS Regions where Amazon SageMaker Unified Studio is available.

Trying It Out

To get started, add an Amazon OpenSearch connection in the data section of your project. Once added, OpenSearch data will appear alongside other project data in the data explorer, and you can immediately run queries in the query editor, explore in notebooks, or incorporate it into visual ETL jobs.

The general procedure for adding a data source connection as described in the official documentation is as follows. Select "Connections" in the navigation pane, then select "Create connection."

From the gallery that appears, select Amazon OpenSearch Service as the connection type.

Enter a descriptive connection name in the "Name" field and configure the parameters according to the connection type. Set your credentials. You can either enter a username and password directly, or use an AWS Secrets Manager secret where credentials are stored.

Select [Create connection], and once validation passes, the connection will be created. You can also press [Test connection] to verify the connection.

The created connection will appear in the data section of the navigation pane, where you can check the connection name, connection type, authorization mode, and connection status.

Closing Thoughts

Amazon SageMaker Unified Studio now supports Amazon OpenSearch as a data source, making it possible to combine and analyze search and log analytics data together with data from Amazon Redshift, Amazon S3, and more, all within a single environment. Correlation analyses that previously required multiple tools—such as joining application logs with transaction data—can now be completed entirely within Studio.

If you have been leveraging OpenSearch for operational log analysis and search but have faced challenges integrating it with your data analytics infrastructure, now is a great opportunity to consider connecting it through Amazon SageMaker Unified Studio.