As enterprises adopt AI-driven architectures, their data pipelines are beginning to look very different from the traditional “ingest, prepare, centralize” model. Today, data must feed a growing ecosystem of intelligent systems running across platforms, clouds, and regions.
AWS-native services such as AWS Glue are designed for workloads that live entirely within AWS. But as organizations push deeper into hybrid, multi-cloud environments, and real-time agentic workflows, teams often run into integration patterns that call for greater functionality, flexibility, portability, and governance than any single cloud service can provide.
To help AWS customers meet these new requirements, IBM watsonx.data integration is now available on the AWS Marketplace.
AWS Marketplace (SaaS) listing: https://aws.amazon.com/marketplace/pp/prodview-2qcxyys5ebzgs
AWS Marketplace (Software) listing: https://aws.amazon.com/marketplace/pp/prodview-rqzsqzmt4fguc
This unlocks a complementary architecture: AWS Glue for AWS-only workloads, and IBM watsonx.data integration for advanced use cases that demand hybrid, governed, multi-pattern integration—all in a unified, enterprise‑grade control plane.
Expanded AWS Footprint in Two Key Regions
Organizations can now deploy the SaaS offering of IBM watsonx.data integration directly on AWS N. Virginia (us-east-1) and AWS Mumbai (ap-south-1): two regions chosen to support global AI and data engineering teams operating under differing data residency, compliance, and latency requirements.
Note: Capabilities vary by region. For the most current regional capability matrix, refer to IBM’s documentation.
This ensures AWS customers can build and scale data pipelines where their data, governance, and regulatory needs reside.
Technical Advantages for AWS Customers
1. Unified Integration Styles Across AWS and Hybrid Environments
IBM watsonx.data integration provides a single experience for building ETL/ELT and real-time streaming integration pipelines—no need to jump between siloed tools.
Organizations with AWS investments gain:
- Reusable pipelines deployable anywhere data resides
- Serverless or remote parallel execution, optimized for performance and locality needs
2. Robust Connectors for Multi-Source, Multi-Cloud Integration
With built-in connectors and prebuilt transformations, teams can:
- Extract data from a wide range of popular AWS services
- Join and transform data from AWS, Azure, GCP, IBM Cloud, on-prem databases
- Deliver curated datasets back into AWS for analytics, ML, or agent workflows
3. Built-In Unstructured Data Integration for RAG + Agentic Workflows
IBM watsonx.data integration supports:
- Ingesting unstructured documents from distributed sources
- Parsing, chunking, metadata extraction, and vectorization prep with prebuilt operators
Note: Unstructured data integration requires the separate acquisition of watsonx.ai Runtime, watsonx.data and (optional for unstructured data governance) watsonx.data intelligence.
4. Data Observability for Faster Detection and Resolution (Available only in AWS N. Virginia us-east-1 as of March 2026)
With data observability, teams can pinpoint unknown data incidents and cut mean time to detection (MTTD) from days to minutes, while improving mean time to resolution (MTTR) from weeks to hours through incident alerting and real-time routing.
IBM watsonx.data integration also helps support data delivery SLAs by surfacing and tracking data quality issues end to end so AWS workloads run on trusted, timely data.
5. Hybrid Execution to Reduce Cost and Latency
With remote parallel execution engines, watsonx.data integration performs joins, transformations, and business logic before data moves across regions or clouds.
This reduces egress cost, latency and pipeline duplication, enabling organizations to optimize pipeline execution for performance and cost efficiency.
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