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★★★☆☆ 21/07/2026

Amazon SageMaker Unified Studio now supports Amazon OpenSearch

Query OpenSearch logs and metrics alongside Redshift and S3 data in one governed workspace—no tool switching required.

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Visual Summary

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What's New

Amazon SageMaker Unified Studio now supports Amazon OpenSearch as a native data source, allowing users to query and analyze search and log analytics data directly within the studio environment. This integration enables data engineers and analysts to combine OpenSearch operational data—such as application logs and metrics—with structured data from Amazon Redshift, Amazon S3, and relational databases in a single, governed workspace. The connection is accessible through the project's data section and surfaces OpenSearch data in the data explorer alongside all other project data assets.

How It Works

  • Connection Setup: Users add an Amazon OpenSearch connection via the "Connections" panel in their SageMaker Unified Studio project, selecting OpenSearch from the connection type gallery and configuring endpoint and authentication parameters (username/password or AWS Secrets Manager secret).
  • Data Discovery: Once connected, OpenSearch indices and data assets appear automatically in the Studio's data explorer, unified with other project data sources for browsing and schema inspection.
  • Query Editor: Users can write and execute queries against OpenSearch data directly in the built-in query editor, enabling ad-hoc analysis without leaving the Studio interface.
  • Notebook Integration: OpenSearch data can be explored and manipulated programmatically within Jupyter-style notebooks, supporting Python-based data science and ML workflows.
  • Visual ETL: OpenSearch can be incorporated as a source or transformation node in visual ETL jobs, enabling no-code/low-code pipeline construction that joins OpenSearch data with other datasets.
  • Cross-Source Joins: The unified environment allows correlating OpenSearch data (e.g., logs, metrics) with transactional or structured data from Redshift, S3, or relational databases within the same workflow.
  • Governance: All OpenSearch connections operate within SageMaker Unified Studio's governed environment, inheriting project-level access controls and data cataloging.

Why It's Important

  • Eliminates Tool Switching: Data engineers previously had to context-switch between OpenSearch Dashboards, query tools, and analytics environments; this integration consolidates those workflows into a single interface, reducing friction and accelerating iteration.
  • Enables Operational + Analytical Correlation: Joining real-time operational data (logs, traces, metrics in OpenSearch) with historical transactional data unlocks insights into system performance, user behavior, and anomaly root causes that were previously difficult to surface.
  • Accelerates Log Analytics Pipelines: Teams building observability or security analytics pipelines can now incorporate OpenSearch log data into ETL jobs and ML models without custom connectors or data movement.
  • Unified Governance: Bringing OpenSearch under the Studio's governed environment means access controls, auditing, and data cataloging apply consistently across all data sources, reducing compliance risk.
  • Reduces Data Duplication: Analysts can query OpenSearch in place rather than exporting data to S3 or Redshift first, lowering storage costs and keeping data fresher.
  • Broadens SageMaker Unified Studio's Data Ecosystem: This addition strengthens the platform's value proposition as a true single-pane-of-glass for heterogeneous data environments.

How It's Different

  • Native Studio Integration vs. External Tools: Unlike using OpenSearch Dashboards or custom API calls from notebooks, this integration surfaces OpenSearch as a first-class data source within SageMaker Unified Studio's data explorer, query editor, and ETL designer.
  • Cross-Source Joins Without ETL Middleware: Traditional approaches require extracting OpenSearch data to S3 or a data warehouse before joining with structured data; this integration enables direct cross-source querying within the Studio, reducing pipeline complexity.
  • Governed Access vs. Ad-Hoc Connectivity: Connecting to OpenSearch through the Studio applies project-level governance and cataloging, whereas direct OpenSearch connections from notebooks or external tools bypass centralized access controls.
  • Visual ETL Support: Most OpenSearch integrations in analytics platforms are read-only query connectors; SageMaker Unified Studio allows OpenSearch to be incorporated into visual ETL job graphs, enabling richer pipeline orchestration.
  • Unified Credential Management: Authentication can leverage AWS Secrets Manager through the Studio's connection framework, providing centralized, auditable credential management rather than hardcoded credentials in notebooks or scripts.

When to Prefer It

  • Log and Metrics Correlation: When you need to join application logs or infrastructure metrics stored in OpenSearch with transactional records in Redshift or RDS to diagnose performance issues or understand user behavior patterns.
  • Observability Pipelines: When building data pipelines that enrich or aggregate OpenSearch-stored traces, logs, and metrics alongside structured business data for unified observability dashboards or ML-based anomaly detection.
  • Security Analytics: When correlating security event logs in OpenSearch with user activity data from relational databases to identify threats or compliance violations within a governed environment.
  • Real-Time + Batch Hybrid Workflows: When your use case requires combining near-real-time search/analytics data from OpenSearch with batch-processed structured datasets in a single ETL or ML pipeline.
  • Teams Already Using SageMaker Unified Studio: When your organization has standardized on SageMaker Unified Studio for data and ML workflows and wants to avoid introducing a separate tool to access OpenSearch data.
  • Governed Multi-Source Environments: When data governance, access control, and auditability across all data sources—including OpenSearch—are organizational requirements that must be enforced centrally.

Availability

  • GA Status: Generally available as of July 21, 2026; no preview or beta designation indicated.
  • Supported Regions: Available in all 15 AWS Regions where SageMaker Unified Studio is supported: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), Europe (Frankfurt), Europe (London), Europe (Paris), Europe (Stockholm), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Mumbai), Canada (Central), and South America (São Paulo).
  • Pricing: No separate charge announced for the OpenSearch connection itself; standard Amazon SageMaker Unified Studio and Amazon OpenSearch Service pricing applies for compute, storage, and query execution.
  • Prerequisites: Requires an existing Amazon OpenSearch Service domain and a SageMaker Unified Studio project; VPC configuration may be required depending on network topology (consistent with other data source connections in the Studio).
  • Documentation: Setup instructions available in the SageMaker Unified Studio User Guide under "Connecting to a new data source."

Tags

Servicessagemaker-unified-studioopensearch
Typeintegration
Conceptsdata-analyticsmlops
Use Casesenterprise
GeographyGlobal

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