IBM is a Leader
See why in the Gartner 2020 Magic Quadrant for Data Integration Tools.
AI-powered data integration. Anywhere.
Your AI and analytics are only as good as the data that fuels them. With a modern container-based architecture, IBM® DataStage® for IBM Cloud Pak® for Data delivers that high-quality data. It combines industry-leading data integration with DataOps, governance and analytics on a single data and AI platform.
Automation accelerates administrative tasks to help reduce TCO. AI-based design accelerators and out-of-the-box integration with DataOps and data science services speed AI innovation. Parallelism and multicloud integration let you deliver trusted data at scale across hybrid or multicloud environments.
DataStage for IBM Cloud Pak for Data
Multiple deployment options
Full spectrum of data and AI services
Manage the data and analytics lifecycle on the IBM Cloud Pak for Data platform. Services include data science, event messaging, data virtualization and data warehousing.
Parallel engine and automated load balancing
Process data at scale by optimizing ETL performance with a best-in-breed parallel engine and load balancing that maximizes throughput.
Metadata support for policy-driven data access
Protect sensitive data with metadata exchange using IBM Watson Knowledge Catalog. Use data lineage to see how data flows through transformation and integration.
Automated delivery pipelines for production
Automate continuous integration/continuous delivery (CI/CD) job pipelines from dev to test to production and help reduce development costs.
Extensive set of prebuilt connectors and stages
Use prebuilt connectivity and stages to move data between multiple cloud sources and data warehouses, such as IBM Netezza and IBM Db2 Warehouse on Cloud.
IBM DataStage Flow Designer
Increase developer productivity with machine learning-assisted design in a user-friendly interface, helping cut development costs.
In-flight data quality
Trust data delivery using IBM InfoSphere QualityStage to automatically resolve quality issues when data is ingested by target environments.
Automated failure detection
Reduce infrastructure management effort 65% - 85% (2), letting users focus on higher value tasks.
Reusable job templates
Auto-generate jobs and use custom rules to enforce patterns.
Webinar series: Go deeper on DataStage for IBM Cloud Pak for Data
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¹Based on IBM internal analysis of client data. Individual client results may vary.
²Forrester, New Technology: The Projected Total Economic Impact Of IBM Cloud Pak For Data (PDF, 1.3 MB), February 2020